forked from bartvdbraak/blender
cf5e979fb4
Implements an automatic keyframe selection algorithm which uses couple of approaches to find out best keyframes candidates: - First, slightly modifier Pollefeys's criteria is used, which limits correspondence ration from 80% to 100%. This allows to reject keyframe candidate early without doing heavy math in cases there're not much common features with first keyframe. - Second step is based on Geometric Robust Information Criteria (aka GRIC), which checks whether features motion between candidate keyframes is better defined by homography or fundamental matrices. To be a good keyframe candidate, fundamental matrix need to define motion better than homography (in this case F-GRIC will be smaller than H-GRIC). This two criteria are well described in this paper: http://www.cs.ait.ac.th/~mdailey/papers/Tahir-KeyFrame.pdf - Final step is based on estimating reconstruction error of a full-scene solution using candidate keyframes. This part is based on the following paper: ftp://ftp.tnt.uni-hannover.de/pub/papers/2004/ECCV2004-TTHBAW.pdf This step requires reconstruction using candidate keyframes and obtaining covariance matrix of 3D points positions. Reconstruction was done pretty much straightforward using other simple pipeline routines, and for covariance estimation pseudo-inverse of Hessian is used, which is in this case (J^T * J)+, where + denotes pseudo-inverse. Jacobian matrix is estimating using Ceres evaluate API. This is also crucial to get rid of possible gauge ambiguity, which is in our case made by zero-ing 7 (by gauge freedoms number) eigen values in pseudo-inverse. There're still room for improving and optimizing the code, but we need some point to start with anyway :) Thanks to Keir Mierle and Sameer Agarwal who assisted a lot to make this feature working.
1081 lines
35 KiB
C++
1081 lines
35 KiB
C++
/*
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* ***** BEGIN GPL LICENSE BLOCK *****
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*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* as published by the Free Software Foundation; either version 2
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* of the License, or (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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*
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* The Original Code is Copyright (C) 2011 Blender Foundation.
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* All rights reserved.
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*
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* Contributor(s): Blender Foundation,
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* Sergey Sharybin
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*
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* ***** END GPL LICENSE BLOCK *****
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*/
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#ifdef WITH_LIBMV
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/* define this to generate PNG images with content of search areas
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tracking between which failed */
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#undef DUMP_FAILURE
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/* define this to generate PNG images with content of search areas
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on every itteration of tracking */
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#undef DUMP_ALWAYS
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#include "libmv-capi.h"
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#include <cstdlib>
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#include <cassert>
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#if defined(DUMP_FAILURE) || defined (DUMP_ALWAYS)
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# include <png.h>
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#endif
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#include "libmv/logging/logging.h"
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#include "libmv/tracking/track_region.h"
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#include "libmv/simple_pipeline/callbacks.h"
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#include "libmv/simple_pipeline/tracks.h"
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#include "libmv/simple_pipeline/initialize_reconstruction.h"
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#include "libmv/simple_pipeline/bundle.h"
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#include "libmv/simple_pipeline/detect.h"
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#include "libmv/simple_pipeline/pipeline.h"
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#include "libmv/simple_pipeline/camera_intrinsics.h"
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#include "libmv/simple_pipeline/modal_solver.h"
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#include "libmv/simple_pipeline/reconstruction_scale.h"
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#include "libmv/simple_pipeline/keyframe_selection.h"
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#ifdef _MSC_VER
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# define snprintf _snprintf
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#endif
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typedef struct libmv_Reconstruction {
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libmv::EuclideanReconstruction reconstruction;
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/* used for per-track average error calculation after reconstruction */
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libmv::Tracks tracks;
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libmv::CameraIntrinsics intrinsics;
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double error;
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} libmv_Reconstruction;
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typedef struct libmv_Features {
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int count, margin;
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libmv::Feature *features;
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} libmv_Features;
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/* ************ Logging ************ */
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void libmv_initLogging(const char *argv0)
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{
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/* Make it so FATAL messages are always print into console */
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char severity_fatal[32];
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snprintf(severity_fatal, sizeof(severity_fatal), "%d",
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google::GLOG_FATAL);
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google::InitGoogleLogging(argv0);
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google::SetCommandLineOption("logtostderr", "1");
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google::SetCommandLineOption("v", "0");
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google::SetCommandLineOption("stderrthreshold", severity_fatal);
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google::SetCommandLineOption("minloglevel", severity_fatal);
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}
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void libmv_startDebugLogging(void)
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{
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google::SetCommandLineOption("logtostderr", "1");
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google::SetCommandLineOption("v", "2");
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google::SetCommandLineOption("stderrthreshold", "1");
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google::SetCommandLineOption("minloglevel", "0");
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}
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void libmv_setLoggingVerbosity(int verbosity)
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{
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char val[10];
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snprintf(val, sizeof(val), "%d", verbosity);
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google::SetCommandLineOption("v", val);
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}
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/* ************ Utility ************ */
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static void floatBufToImage(const float *buf, int width, int height, int channels, libmv::FloatImage *image)
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{
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int x, y, k, a = 0;
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image->Resize(height, width, channels);
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for (y = 0; y < height; y++) {
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for (x = 0; x < width; x++) {
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for (k = 0; k < channels; k++) {
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(*image)(y, x, k) = buf[a++];
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}
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}
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}
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}
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static void imageToFloatBuf(const libmv::FloatImage *image, int channels, float *buf)
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{
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int x, y, k, a = 0;
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for (y = 0; y < image->Height(); y++) {
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for (x = 0; x < image->Width(); x++) {
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for (k = 0; k < channels; k++) {
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buf[a++] = (*image)(y, x, k);
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}
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}
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}
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}
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#if defined(DUMP_FAILURE) || defined (DUMP_ALWAYS)
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static void savePNGImage(png_bytep *row_pointers, int width, int height, int depth, int color_type,
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const char *file_name)
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{
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png_infop info_ptr;
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png_structp png_ptr;
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FILE *fp = fopen(file_name, "wb");
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if (!fp)
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return;
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/* Initialize stuff */
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png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING, NULL, NULL, NULL);
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info_ptr = png_create_info_struct(png_ptr);
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if (setjmp(png_jmpbuf(png_ptr))) {
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fclose(fp);
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return;
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}
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png_init_io(png_ptr, fp);
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/* write header */
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if (setjmp(png_jmpbuf(png_ptr))) {
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fclose(fp);
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return;
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}
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png_set_IHDR(png_ptr, info_ptr, width, height,
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depth, color_type, PNG_INTERLACE_NONE,
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PNG_COMPRESSION_TYPE_BASE, PNG_FILTER_TYPE_BASE);
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png_write_info(png_ptr, info_ptr);
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/* write bytes */
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if (setjmp(png_jmpbuf(png_ptr))) {
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fclose(fp);
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return;
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}
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png_write_image(png_ptr, row_pointers);
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/* end write */
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if (setjmp(png_jmpbuf(png_ptr))) {
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fclose(fp);
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return;
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}
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png_write_end(png_ptr, NULL);
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fclose(fp);
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}
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static void saveImage(const char *prefix, libmv::FloatImage image, int x0, int y0)
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{
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int x, y;
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png_bytep *row_pointers;
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row_pointers= (png_bytep*)malloc(sizeof(png_bytep)*image.Height());
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for (y = 0; y < image.Height(); y++) {
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row_pointers[y]= (png_bytep)malloc(sizeof(png_byte)*4*image.Width());
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for (x = 0; x < image.Width(); x++) {
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if (x0 == x && image.Height() - y0 - 1 == y) {
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row_pointers[y][x*4+0]= 255;
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row_pointers[y][x*4+1]= 0;
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row_pointers[y][x*4+2]= 0;
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row_pointers[y][x*4+3]= 255;
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}
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else {
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float pixel = image(image.Height() - y - 1, x, 0);
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row_pointers[y][x*4+0]= pixel*255;
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row_pointers[y][x*4+1]= pixel*255;
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row_pointers[y][x*4+2]= pixel*255;
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row_pointers[y][x*4+3]= 255;
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}
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}
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}
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{
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static int a= 0;
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char buf[128];
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snprintf(buf, sizeof(buf), "%s_%02d.png", prefix, ++a);
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savePNGImage(row_pointers, image.Width(), image.Height(), 8, PNG_COLOR_TYPE_RGBA, buf);
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}
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for (y = 0; y < image.Height(); y++) {
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free(row_pointers[y]);
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}
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free(row_pointers);
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}
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static void saveBytesImage(const char *prefix, unsigned char *data, int width, int height)
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{
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int x, y;
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png_bytep *row_pointers;
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row_pointers= (png_bytep*)malloc(sizeof(png_bytep)*height);
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for (y = 0; y < height; y++) {
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row_pointers[y]= (png_bytep)malloc(sizeof(png_byte)*4*width);
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for (x = 0; x < width; x++) {
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char pixel = data[width*y+x];
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row_pointers[y][x*4+0]= pixel;
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row_pointers[y][x*4+1]= pixel;
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row_pointers[y][x*4+2]= pixel;
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row_pointers[y][x*4+3]= 255;
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}
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}
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{
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static int a = 0;
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char buf[128];
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snprintf(buf, sizeof(buf), "%s_%02d.png", prefix, ++a);
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savePNGImage(row_pointers, width, height, 8, PNG_COLOR_TYPE_RGBA, buf);
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}
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for (y = 0; y < height; y++) {
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free(row_pointers[y]);
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}
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free(row_pointers);
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}
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#endif
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/* ************ Planar tracker ************ */
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/* TrackRegion (new planar tracker) */
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int libmv_trackRegion(const struct libmv_trackRegionOptions *options,
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const float *image1, int image1_width, int image1_height,
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const float *image2, int image2_width, int image2_height,
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const double *x1, const double *y1,
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struct libmv_trackRegionResult *result,
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double *x2, double *y2)
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{
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double xx1[5], yy1[5];
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double xx2[5], yy2[5];
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bool tracking_result = false;
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/* Convert to doubles for the libmv api. The four corners and the center. */
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for (int i = 0; i < 5; ++i) {
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xx1[i] = x1[i];
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yy1[i] = y1[i];
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xx2[i] = x2[i];
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yy2[i] = y2[i];
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}
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libmv::TrackRegionOptions track_region_options;
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libmv::FloatImage image1_mask;
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switch (options->motion_model) {
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#define LIBMV_CONVERT(the_model) \
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case libmv::TrackRegionOptions::the_model: \
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track_region_options.mode = libmv::TrackRegionOptions::the_model; \
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break;
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LIBMV_CONVERT(TRANSLATION)
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LIBMV_CONVERT(TRANSLATION_ROTATION)
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LIBMV_CONVERT(TRANSLATION_SCALE)
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LIBMV_CONVERT(TRANSLATION_ROTATION_SCALE)
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LIBMV_CONVERT(AFFINE)
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LIBMV_CONVERT(HOMOGRAPHY)
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#undef LIBMV_CONVERT
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}
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track_region_options.minimum_correlation = options->minimum_correlation;
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track_region_options.max_iterations = options->num_iterations;
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track_region_options.sigma = options->sigma;
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track_region_options.num_extra_points = 1;
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track_region_options.image1_mask = NULL;
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track_region_options.use_brute_initialization = options->use_brute;
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track_region_options.use_normalized_intensities = options->use_normalization;
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if (options->image1_mask) {
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floatBufToImage(options->image1_mask, image1_width, image1_height, 1, &image1_mask);
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track_region_options.image1_mask = &image1_mask;
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}
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/* Convert from raw float buffers to libmv's FloatImage. */
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libmv::FloatImage old_patch, new_patch;
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floatBufToImage(image1, image1_width, image1_height, 1, &old_patch);
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floatBufToImage(image2, image2_width, image2_height, 1, &new_patch);
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libmv::TrackRegionResult track_region_result;
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libmv::TrackRegion(old_patch, new_patch, xx1, yy1, track_region_options, xx2, yy2, &track_region_result);
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/* Convert to floats for the blender api. */
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for (int i = 0; i < 5; ++i) {
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x2[i] = xx2[i];
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y2[i] = yy2[i];
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}
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/* TODO(keir): Update the termination string with failure details. */
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if (track_region_result.termination == libmv::TrackRegionResult::PARAMETER_TOLERANCE ||
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track_region_result.termination == libmv::TrackRegionResult::FUNCTION_TOLERANCE ||
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track_region_result.termination == libmv::TrackRegionResult::GRADIENT_TOLERANCE ||
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track_region_result.termination == libmv::TrackRegionResult::NO_CONVERGENCE)
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{
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tracking_result = true;
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}
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#if defined(DUMP_FAILURE) || defined(DUMP_ALWAYS)
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#if defined(DUMP_ALWAYS)
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{
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#else
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if (!tracking_result) {
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#endif
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saveImage("old_patch", old_patch, x1[4], y1[4]);
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saveImage("new_patch", new_patch, x2[4], y2[4]);
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if (options->image1_mask)
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saveImage("mask", image1_mask, x2[4], y2[4]);
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}
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#endif
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return tracking_result;
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}
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void libmv_samplePlanarPatch(const float *image, int width, int height,
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int channels, const double *xs, const double *ys,
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int num_samples_x, int num_samples_y,
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const float *mask, float *patch,
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double *warped_position_x, double *warped_position_y)
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{
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libmv::FloatImage libmv_image, libmv_patch, libmv_mask;
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libmv::FloatImage *libmv_mask_for_sample = NULL;
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floatBufToImage(image, width, height, channels, &libmv_image);
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if (mask) {
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floatBufToImage(mask, width, height, 1, &libmv_mask);
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libmv_mask_for_sample = &libmv_mask;
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}
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libmv::SamplePlanarPatch(libmv_image, xs, ys, num_samples_x, num_samples_y,
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libmv_mask_for_sample, &libmv_patch,
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warped_position_x, warped_position_y);
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imageToFloatBuf(&libmv_patch, channels, patch);
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}
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/* ************ Tracks ************ */
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libmv_Tracks *libmv_tracksNew(void)
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{
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libmv::Tracks *libmv_tracks = new libmv::Tracks();
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return (libmv_Tracks *)libmv_tracks;
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}
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void libmv_tracksInsert(struct libmv_Tracks *libmv_tracks, int image, int track, double x, double y)
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{
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((libmv::Tracks*)libmv_tracks)->Insert(image, track, x, y);
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}
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void libmv_tracksDestroy(libmv_Tracks *libmv_tracks)
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{
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delete (libmv::Tracks*)libmv_tracks;
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}
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/* ************ Reconstruction solver ************ */
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class ReconstructUpdateCallback : public libmv::ProgressUpdateCallback {
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public:
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ReconstructUpdateCallback(reconstruct_progress_update_cb progress_update_callback,
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void *callback_customdata)
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{
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progress_update_callback_ = progress_update_callback;
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callback_customdata_ = callback_customdata;
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}
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void invoke(double progress, const char *message)
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{
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if(progress_update_callback_) {
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progress_update_callback_(callback_customdata_, progress, message);
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}
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}
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protected:
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reconstruct_progress_update_cb progress_update_callback_;
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void *callback_customdata_;
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};
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static void libmv_solveRefineIntrinsics(const libmv::Tracks &tracks,
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const int refine_intrinsics,
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const int bundle_constraints,
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reconstruct_progress_update_cb progress_update_callback,
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void *callback_customdata,
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libmv::EuclideanReconstruction *reconstruction,
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libmv::CameraIntrinsics *intrinsics)
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{
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/* only a few combinations are supported but trust the caller */
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int bundle_intrinsics = 0;
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if (refine_intrinsics & LIBMV_REFINE_FOCAL_LENGTH) {
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bundle_intrinsics |= libmv::BUNDLE_FOCAL_LENGTH;
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}
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if (refine_intrinsics & LIBMV_REFINE_PRINCIPAL_POINT) {
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bundle_intrinsics |= libmv::BUNDLE_PRINCIPAL_POINT;
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}
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if (refine_intrinsics & LIBMV_REFINE_RADIAL_DISTORTION_K1) {
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bundle_intrinsics |= libmv::BUNDLE_RADIAL_K1;
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}
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if (refine_intrinsics & LIBMV_REFINE_RADIAL_DISTORTION_K2) {
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bundle_intrinsics |= libmv::BUNDLE_RADIAL_K2;
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}
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progress_update_callback(callback_customdata, 1.0, "Refining solution");
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libmv::EuclideanBundleCommonIntrinsics(tracks,
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bundle_intrinsics,
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bundle_constraints,
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reconstruction,
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intrinsics);
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}
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|
|
static void cameraIntrinsicsFromOptions(const libmv_cameraIntrinsicsOptions *camera_intrinsics_options,
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libmv::CameraIntrinsics *camera_intrinsics)
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{
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camera_intrinsics->SetFocalLength(camera_intrinsics_options->focal_length,
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camera_intrinsics_options->focal_length);
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camera_intrinsics->SetPrincipalPoint(camera_intrinsics_options->principal_point_x,
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camera_intrinsics_options->principal_point_y);
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camera_intrinsics->SetRadialDistortion(camera_intrinsics_options->k1,
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camera_intrinsics_options->k2,
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camera_intrinsics_options->k3);
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camera_intrinsics->SetImageSize(camera_intrinsics_options->image_width,
|
|
camera_intrinsics_options->image_height);
|
|
}
|
|
|
|
static libmv::Tracks getNormalizedTracks(const libmv::Tracks &tracks, const libmv::CameraIntrinsics &camera_intrinsics)
|
|
{
|
|
libmv::vector<libmv::Marker> markers = tracks.AllMarkers();
|
|
|
|
for (int i = 0; i < markers.size(); ++i) {
|
|
camera_intrinsics.InvertIntrinsics(markers[i].x, markers[i].y,
|
|
&(markers[i].x), &(markers[i].y));
|
|
}
|
|
|
|
return libmv::Tracks(markers);
|
|
}
|
|
|
|
static void finishReconstruction(const libmv::Tracks &tracks, const libmv::CameraIntrinsics &camera_intrinsics,
|
|
libmv_Reconstruction *libmv_reconstruction,
|
|
reconstruct_progress_update_cb progress_update_callback,
|
|
void *callback_customdata)
|
|
{
|
|
libmv::EuclideanReconstruction &reconstruction = libmv_reconstruction->reconstruction;
|
|
|
|
/* reprojection error calculation */
|
|
progress_update_callback(callback_customdata, 1.0, "Finishing solution");
|
|
libmv_reconstruction->tracks = tracks;
|
|
libmv_reconstruction->error = libmv::EuclideanReprojectionError(tracks, reconstruction, camera_intrinsics);
|
|
}
|
|
|
|
static bool selectTwoKeyframesBasedOnGRICAndVariance(
|
|
libmv::Tracks &tracks,
|
|
libmv::Tracks &normalized_tracks,
|
|
libmv::CameraIntrinsics &camera_intrinsics,
|
|
libmv::ReconstructionOptions &reconstruction_options,
|
|
int &keyframe1,
|
|
int &keyframe2)
|
|
{
|
|
libmv::vector<int> keyframes;
|
|
|
|
/* Get list of all keyframe candidates first. */
|
|
SelectkeyframesBasedOnGRICAndVariance(normalized_tracks,
|
|
camera_intrinsics,
|
|
keyframes);
|
|
|
|
if (keyframes.size() < 2) {
|
|
LG << "Not enough keyframes detected by GRIC";
|
|
return false;
|
|
}
|
|
else if (keyframes.size() == 2) {
|
|
keyframe1 = keyframes[0];
|
|
keyframe2 = keyframes[1];
|
|
return true;
|
|
}
|
|
|
|
/* Now choose two keyframes with minimal reprojection error after initial
|
|
* reconstruction choose keyframes with the least reprojection error after
|
|
* solving from two candidate keyframes.
|
|
*
|
|
* In fact, currently libmv returns single pair only, so this code will
|
|
* not actually run. But in the future this could change, so let's stay
|
|
* prepared.
|
|
*/
|
|
int previous_keyframe = keyframes[0];
|
|
double best_error = std::numeric_limits<double>::max();
|
|
for (int i = 1; i < keyframes.size(); i++) {
|
|
libmv::EuclideanReconstruction reconstruction;
|
|
int current_keyframe = keyframes[i];
|
|
|
|
libmv::vector<libmv::Marker> keyframe_markers =
|
|
normalized_tracks.MarkersForTracksInBothImages(previous_keyframe,
|
|
current_keyframe);
|
|
|
|
libmv::Tracks keyframe_tracks(keyframe_markers);
|
|
|
|
/* get a solution from two keyframes only */
|
|
libmv::EuclideanReconstructTwoFrames(keyframe_markers, &reconstruction);
|
|
libmv::EuclideanBundle(keyframe_tracks, &reconstruction);
|
|
libmv::EuclideanCompleteReconstruction(reconstruction_options,
|
|
keyframe_tracks,
|
|
&reconstruction, NULL);
|
|
|
|
double current_error =
|
|
libmv::EuclideanReprojectionError(tracks,
|
|
reconstruction,
|
|
camera_intrinsics);
|
|
|
|
LG << "Error between " << previous_keyframe
|
|
<< " and " << current_keyframe
|
|
<< ": " << current_error;
|
|
|
|
if (current_error < best_error) {
|
|
best_error = current_error;
|
|
keyframe1 = previous_keyframe;
|
|
keyframe2 = current_keyframe;
|
|
}
|
|
|
|
previous_keyframe = current_keyframe;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
libmv_Reconstruction *libmv_solveReconstruction(const libmv_Tracks *libmv_tracks,
|
|
const libmv_cameraIntrinsicsOptions *libmv_camera_intrinsics_options,
|
|
libmv_reconstructionOptions *libmv_reconstruction_options,
|
|
reconstruct_progress_update_cb progress_update_callback,
|
|
void *callback_customdata)
|
|
{
|
|
libmv_Reconstruction *libmv_reconstruction = new libmv_Reconstruction();
|
|
|
|
libmv::Tracks &tracks = *((libmv::Tracks *) libmv_tracks);
|
|
libmv::EuclideanReconstruction &reconstruction = libmv_reconstruction->reconstruction;
|
|
libmv::CameraIntrinsics &camera_intrinsics = libmv_reconstruction->intrinsics;
|
|
|
|
ReconstructUpdateCallback update_callback =
|
|
ReconstructUpdateCallback(progress_update_callback, callback_customdata);
|
|
|
|
/* Retrieve reconstruction options from C-API to libmv API */
|
|
cameraIntrinsicsFromOptions(libmv_camera_intrinsics_options, &camera_intrinsics);
|
|
|
|
libmv::ReconstructionOptions reconstruction_options;
|
|
reconstruction_options.success_threshold = libmv_reconstruction_options->success_threshold;
|
|
reconstruction_options.use_fallback_reconstruction = libmv_reconstruction_options->use_fallback_reconstruction;
|
|
|
|
/* Invert the camera intrinsics */
|
|
libmv::Tracks normalized_tracks = getNormalizedTracks(tracks, camera_intrinsics);
|
|
|
|
/* keyframe selection */
|
|
int keyframe1 = libmv_reconstruction_options->keyframe1,
|
|
keyframe2 = libmv_reconstruction_options->keyframe2;
|
|
|
|
if (libmv_reconstruction_options->select_keyframes) {
|
|
LG << "Using automatic keyframe selection";
|
|
|
|
update_callback.invoke(0, "Selecting keyframes");
|
|
|
|
selectTwoKeyframesBasedOnGRICAndVariance(tracks,
|
|
normalized_tracks,
|
|
camera_intrinsics,
|
|
reconstruction_options,
|
|
keyframe1,
|
|
keyframe2);
|
|
|
|
/* so keyframes in the interface would be updated */
|
|
libmv_reconstruction_options->keyframe1 = keyframe1;
|
|
libmv_reconstruction_options->keyframe2 = keyframe2;
|
|
}
|
|
|
|
/* actual reconstruction */
|
|
LG << "frames to init from: " << keyframe1 << " " << keyframe2;
|
|
|
|
libmv::vector<libmv::Marker> keyframe_markers =
|
|
normalized_tracks.MarkersForTracksInBothImages(keyframe1, keyframe2);
|
|
|
|
LG << "number of markers for init: " << keyframe_markers.size();
|
|
|
|
update_callback.invoke(0, "Initial reconstruction");
|
|
|
|
libmv::EuclideanReconstructTwoFrames(keyframe_markers, &reconstruction);
|
|
libmv::EuclideanBundle(normalized_tracks, &reconstruction);
|
|
libmv::EuclideanCompleteReconstruction(reconstruction_options, normalized_tracks,
|
|
&reconstruction, &update_callback);
|
|
|
|
/* refinement */
|
|
if (libmv_reconstruction_options->refine_intrinsics) {
|
|
libmv_solveRefineIntrinsics(tracks,
|
|
libmv_reconstruction_options->refine_intrinsics,
|
|
libmv::BUNDLE_NO_CONSTRAINTS,
|
|
progress_update_callback,
|
|
callback_customdata,
|
|
&reconstruction,
|
|
&camera_intrinsics);
|
|
}
|
|
|
|
/* set reconstruction scale to unity */
|
|
libmv::EuclideanScaleToUnity(&reconstruction);
|
|
|
|
/* finish reconstruction */
|
|
finishReconstruction(tracks, camera_intrinsics, libmv_reconstruction,
|
|
progress_update_callback, callback_customdata);
|
|
|
|
return (libmv_Reconstruction *)libmv_reconstruction;
|
|
}
|
|
|
|
struct libmv_Reconstruction *libmv_solveModal(const libmv_Tracks *libmv_tracks,
|
|
const libmv_cameraIntrinsicsOptions *libmv_camera_intrinsics_options,
|
|
const libmv_reconstructionOptions *libmv_reconstruction_options,
|
|
reconstruct_progress_update_cb progress_update_callback,
|
|
void *callback_customdata)
|
|
{
|
|
libmv_Reconstruction *libmv_reconstruction = new libmv_Reconstruction();
|
|
|
|
libmv::Tracks &tracks = *((libmv::Tracks *) libmv_tracks);
|
|
libmv::EuclideanReconstruction &reconstruction = libmv_reconstruction->reconstruction;
|
|
libmv::CameraIntrinsics &camera_intrinsics = libmv_reconstruction->intrinsics;
|
|
|
|
ReconstructUpdateCallback update_callback =
|
|
ReconstructUpdateCallback(progress_update_callback, callback_customdata);
|
|
|
|
cameraIntrinsicsFromOptions(libmv_camera_intrinsics_options, &camera_intrinsics);
|
|
|
|
/* Invert the camera intrinsics. */
|
|
libmv::Tracks normalized_tracks = getNormalizedTracks(tracks, camera_intrinsics);
|
|
|
|
/* Actual reconstruction. */
|
|
libmv::ModalSolver(normalized_tracks, &reconstruction, &update_callback);
|
|
|
|
libmv::CameraIntrinsics empty_intrinsics;
|
|
libmv::EuclideanBundleCommonIntrinsics(normalized_tracks,
|
|
libmv::BUNDLE_NO_INTRINSICS,
|
|
libmv::BUNDLE_NO_TRANSLATION,
|
|
&reconstruction,
|
|
&empty_intrinsics);
|
|
|
|
/* Refinement. */
|
|
if (libmv_reconstruction_options->refine_intrinsics) {
|
|
libmv_solveRefineIntrinsics(tracks,
|
|
libmv_reconstruction_options->refine_intrinsics,
|
|
libmv::BUNDLE_NO_TRANSLATION,
|
|
progress_update_callback, callback_customdata,
|
|
&reconstruction,
|
|
&camera_intrinsics);
|
|
}
|
|
|
|
/* Finish reconstruction. */
|
|
finishReconstruction(tracks, camera_intrinsics, libmv_reconstruction,
|
|
progress_update_callback, callback_customdata);
|
|
|
|
return (libmv_Reconstruction *)libmv_reconstruction;
|
|
}
|
|
|
|
int libmv_reporojectionPointForTrack(const libmv_Reconstruction *libmv_reconstruction, int track, double pos[3])
|
|
{
|
|
const libmv::EuclideanReconstruction *reconstruction = &libmv_reconstruction->reconstruction;
|
|
const libmv::EuclideanPoint *point = reconstruction->PointForTrack(track);
|
|
|
|
if(point) {
|
|
pos[0] = point->X[0];
|
|
pos[1] = point->X[2];
|
|
pos[2] = point->X[1];
|
|
|
|
return 1;
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
static libmv::Marker ProjectMarker(const libmv::EuclideanPoint &point,
|
|
const libmv::EuclideanCamera &camera,
|
|
const libmv::CameraIntrinsics &intrinsics)
|
|
{
|
|
libmv::Vec3 projected = camera.R * point.X + camera.t;
|
|
projected /= projected(2);
|
|
|
|
libmv::Marker reprojected_marker;
|
|
intrinsics.ApplyIntrinsics(projected(0), projected(1), &reprojected_marker.x, &reprojected_marker.y);
|
|
|
|
reprojected_marker.image = camera.image;
|
|
reprojected_marker.track = point.track;
|
|
|
|
return reprojected_marker;
|
|
}
|
|
|
|
double libmv_reporojectionErrorForTrack(const libmv_Reconstruction *libmv_reconstruction, int track)
|
|
{
|
|
const libmv::EuclideanReconstruction *reconstruction = &libmv_reconstruction->reconstruction;
|
|
const libmv::CameraIntrinsics *intrinsics = &libmv_reconstruction->intrinsics;
|
|
libmv::vector<libmv::Marker> markers = libmv_reconstruction->tracks.MarkersForTrack(track);
|
|
|
|
int num_reprojected = 0;
|
|
double total_error = 0.0;
|
|
|
|
for (int i = 0; i < markers.size(); ++i) {
|
|
const libmv::EuclideanCamera *camera = reconstruction->CameraForImage(markers[i].image);
|
|
const libmv::EuclideanPoint *point = reconstruction->PointForTrack(markers[i].track);
|
|
|
|
if (!camera || !point) {
|
|
continue;
|
|
}
|
|
|
|
num_reprojected++;
|
|
|
|
libmv::Marker reprojected_marker = ProjectMarker(*point, *camera, *intrinsics);
|
|
double ex = reprojected_marker.x - markers[i].x;
|
|
double ey = reprojected_marker.y - markers[i].y;
|
|
|
|
total_error += sqrt(ex*ex + ey*ey);
|
|
}
|
|
|
|
return total_error / num_reprojected;
|
|
}
|
|
|
|
double libmv_reporojectionErrorForImage(const libmv_Reconstruction *libmv_reconstruction, int image)
|
|
{
|
|
const libmv::EuclideanReconstruction *reconstruction = &libmv_reconstruction->reconstruction;
|
|
const libmv::CameraIntrinsics *intrinsics = &libmv_reconstruction->intrinsics;
|
|
libmv::vector<libmv::Marker> markers = libmv_reconstruction->tracks.MarkersInImage(image);
|
|
const libmv::EuclideanCamera *camera = reconstruction->CameraForImage(image);
|
|
int num_reprojected = 0;
|
|
double total_error = 0.0;
|
|
|
|
if (!camera)
|
|
return 0;
|
|
|
|
for (int i = 0; i < markers.size(); ++i) {
|
|
const libmv::EuclideanPoint *point = reconstruction->PointForTrack(markers[i].track);
|
|
|
|
if (!point) {
|
|
continue;
|
|
}
|
|
|
|
num_reprojected++;
|
|
|
|
libmv::Marker reprojected_marker = ProjectMarker(*point, *camera, *intrinsics);
|
|
double ex = reprojected_marker.x - markers[i].x;
|
|
double ey = reprojected_marker.y - markers[i].y;
|
|
|
|
total_error += sqrt(ex*ex + ey*ey);
|
|
}
|
|
|
|
return total_error / num_reprojected;
|
|
}
|
|
|
|
int libmv_reporojectionCameraForImage(const libmv_Reconstruction *libmv_reconstruction,
|
|
int image, double mat[4][4])
|
|
{
|
|
const libmv::EuclideanReconstruction *reconstruction = &libmv_reconstruction->reconstruction;
|
|
const libmv::EuclideanCamera *camera = reconstruction->CameraForImage(image);
|
|
|
|
if(camera) {
|
|
for (int j = 0; j < 3; ++j) {
|
|
for (int k = 0; k < 3; ++k) {
|
|
int l = k;
|
|
|
|
if (k == 1) l = 2;
|
|
else if (k == 2) l = 1;
|
|
|
|
if (j == 2) mat[j][l] = -camera->R(j,k);
|
|
else mat[j][l] = camera->R(j,k);
|
|
}
|
|
mat[j][3]= 0.0;
|
|
}
|
|
|
|
libmv::Vec3 optical_center = -camera->R.transpose() * camera->t;
|
|
|
|
mat[3][0] = optical_center(0);
|
|
mat[3][1] = optical_center(2);
|
|
mat[3][2] = optical_center(1);
|
|
|
|
mat[3][3]= 1.0;
|
|
|
|
return 1;
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
double libmv_reprojectionError(const libmv_Reconstruction *libmv_reconstruction)
|
|
{
|
|
return libmv_reconstruction->error;
|
|
}
|
|
|
|
void libmv_destroyReconstruction(libmv_Reconstruction *libmv_reconstruction)
|
|
{
|
|
delete libmv_reconstruction;
|
|
}
|
|
|
|
/* ************ feature detector ************ */
|
|
|
|
struct libmv_Features *libmv_detectFeaturesFAST(const unsigned char *data,
|
|
int width, int height, int stride,
|
|
int margin, int min_trackness, int min_distance)
|
|
{
|
|
libmv::Feature *features = NULL;
|
|
std::vector<libmv::Feature> v;
|
|
libmv_Features *libmv_features = new libmv_Features();
|
|
int i= 0, count;
|
|
|
|
if(margin) {
|
|
data += margin*stride+margin;
|
|
width -= 2*margin;
|
|
height -= 2*margin;
|
|
}
|
|
|
|
v = libmv::DetectFAST(data, width, height, stride, min_trackness, min_distance);
|
|
|
|
count = v.size();
|
|
|
|
if(count) {
|
|
features= new libmv::Feature[count];
|
|
|
|
for(std::vector<libmv::Feature>::iterator it = v.begin(); it != v.end(); it++) {
|
|
features[i++]= *it;
|
|
}
|
|
}
|
|
|
|
libmv_features->features = features;
|
|
libmv_features->count = count;
|
|
libmv_features->margin = margin;
|
|
|
|
return (libmv_Features *)libmv_features;
|
|
}
|
|
|
|
struct libmv_Features *libmv_detectFeaturesMORAVEC(const unsigned char *data,
|
|
int width, int height, int stride,
|
|
int margin, int count, int min_distance)
|
|
{
|
|
libmv::Feature *features = NULL;
|
|
libmv_Features *libmv_features = new libmv_Features;
|
|
|
|
if(count) {
|
|
if(margin) {
|
|
data += margin*stride+margin;
|
|
width -= 2*margin;
|
|
height -= 2*margin;
|
|
}
|
|
|
|
features = new libmv::Feature[count];
|
|
libmv::DetectMORAVEC(data, stride, width, height, features, &count, min_distance, NULL);
|
|
}
|
|
|
|
libmv_features->count = count;
|
|
libmv_features->margin = margin;
|
|
libmv_features->features = features;
|
|
|
|
return libmv_features;
|
|
}
|
|
|
|
int libmv_countFeatures(const libmv_Features *libmv_features)
|
|
{
|
|
return libmv_features->count;
|
|
}
|
|
|
|
void libmv_getFeature(const libmv_Features *libmv_features, int number, double *x, double *y, double *score, double *size)
|
|
{
|
|
libmv::Feature feature= libmv_features->features[number];
|
|
|
|
*x = feature.x + libmv_features->margin;
|
|
*y = feature.y + libmv_features->margin;
|
|
*score = feature.score;
|
|
*size = feature.size;
|
|
}
|
|
|
|
void libmv_destroyFeatures(libmv_Features *libmv_features)
|
|
{
|
|
if(libmv_features->features)
|
|
delete [] libmv_features->features;
|
|
|
|
delete libmv_features;
|
|
}
|
|
|
|
/* ************ camera intrinsics ************ */
|
|
|
|
struct libmv_CameraIntrinsics *libmv_ReconstructionExtractIntrinsics(libmv_Reconstruction *libmv_Reconstruction)
|
|
{
|
|
return (struct libmv_CameraIntrinsics *)&libmv_Reconstruction->intrinsics;
|
|
}
|
|
|
|
struct libmv_CameraIntrinsics *libmv_CameraIntrinsicsNewEmpty(void)
|
|
{
|
|
libmv::CameraIntrinsics *camera_intrinsics = new libmv::CameraIntrinsics();
|
|
|
|
return (struct libmv_CameraIntrinsics *) camera_intrinsics;
|
|
}
|
|
|
|
struct libmv_CameraIntrinsics *libmv_CameraIntrinsicsNew(const libmv_cameraIntrinsicsOptions *libmv_camera_intrinsics_options)
|
|
{
|
|
libmv::CameraIntrinsics *camera_intrinsics = new libmv::CameraIntrinsics();
|
|
|
|
cameraIntrinsicsFromOptions(libmv_camera_intrinsics_options, camera_intrinsics);
|
|
|
|
return (struct libmv_CameraIntrinsics *) camera_intrinsics;
|
|
}
|
|
|
|
struct libmv_CameraIntrinsics *libmv_CameraIntrinsicsCopy(const libmv_CameraIntrinsics *libmvIntrinsics)
|
|
{
|
|
libmv::CameraIntrinsics *orig_intrinsics = (libmv::CameraIntrinsics *) libmvIntrinsics;
|
|
libmv::CameraIntrinsics *new_intrinsics= new libmv::CameraIntrinsics(*orig_intrinsics);
|
|
|
|
return (struct libmv_CameraIntrinsics *) new_intrinsics;
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsDestroy(struct libmv_CameraIntrinsics *libmvIntrinsics)
|
|
{
|
|
libmv::CameraIntrinsics *intrinsics = (libmv::CameraIntrinsics *) libmvIntrinsics;
|
|
|
|
delete intrinsics;
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsUpdate(const libmv_cameraIntrinsicsOptions *libmv_camera_intrinsics_options,
|
|
libmv_CameraIntrinsics *libmv_intrinsics)
|
|
{
|
|
libmv::CameraIntrinsics *camera_intrinsics = (libmv::CameraIntrinsics *) libmv_intrinsics;
|
|
|
|
double focal_length = libmv_camera_intrinsics_options->focal_length;
|
|
double principal_x = libmv_camera_intrinsics_options->principal_point_x;
|
|
double principal_y = libmv_camera_intrinsics_options->principal_point_y;
|
|
double k1 = libmv_camera_intrinsics_options->k1;
|
|
double k2 = libmv_camera_intrinsics_options->k2;
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double k3 = libmv_camera_intrinsics_options->k3;
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int image_width = libmv_camera_intrinsics_options->image_width;
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int image_height = libmv_camera_intrinsics_options->image_height;
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|
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/* try avoid unnecessary updates so pre-computed distortion grids are not freed */
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|
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if (camera_intrinsics->focal_length() != focal_length)
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camera_intrinsics->SetFocalLength(focal_length, focal_length);
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|
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if (camera_intrinsics->principal_point_x() != principal_x ||
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camera_intrinsics->principal_point_y() != principal_y)
|
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{
|
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camera_intrinsics->SetPrincipalPoint(principal_x, principal_y);
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}
|
|
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if (camera_intrinsics->k1() != k1 ||
|
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camera_intrinsics->k2() != k2 ||
|
|
camera_intrinsics->k3() != k3)
|
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{
|
|
camera_intrinsics->SetRadialDistortion(k1, k2, k3);
|
|
}
|
|
|
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if (camera_intrinsics->image_width() != image_width ||
|
|
camera_intrinsics->image_height() != image_height)
|
|
{
|
|
camera_intrinsics->SetImageSize(image_width, image_height);
|
|
}
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsSetThreads(libmv_CameraIntrinsics *libmv_intrinsics, int threads)
|
|
{
|
|
libmv::CameraIntrinsics *camera_intrinsics = (libmv::CameraIntrinsics *) libmv_intrinsics;
|
|
|
|
camera_intrinsics->SetThreads(threads);
|
|
}
|
|
|
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void libmv_CameraIntrinsicsExtract(const libmv_CameraIntrinsics *libmv_intrinsics, double *focal_length,
|
|
double *principal_x, double *principal_y, double *k1, double *k2, double *k3, int *width, int *height)
|
|
{
|
|
libmv::CameraIntrinsics *camera_intrinsics = (libmv::CameraIntrinsics *) libmv_intrinsics;
|
|
|
|
*focal_length = camera_intrinsics->focal_length();
|
|
*principal_x = camera_intrinsics->principal_point_x();
|
|
*principal_y = camera_intrinsics->principal_point_y();
|
|
*k1 = camera_intrinsics->k1();
|
|
*k2 = camera_intrinsics->k2();
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsUndistortByte(const libmv_CameraIntrinsics *libmv_intrinsics,
|
|
unsigned char *src, unsigned char *dst, int width, int height, float overscan, int channels)
|
|
{
|
|
libmv::CameraIntrinsics *camera_intrinsics = (libmv::CameraIntrinsics *) libmv_intrinsics;
|
|
|
|
camera_intrinsics->Undistort(src, dst, width, height, overscan, channels);
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsUndistortFloat(const libmv_CameraIntrinsics *libmvIntrinsics,
|
|
float *src, float *dst, int width, int height, float overscan, int channels)
|
|
{
|
|
libmv::CameraIntrinsics *intrinsics = (libmv::CameraIntrinsics *) libmvIntrinsics;
|
|
|
|
intrinsics->Undistort(src, dst, width, height, overscan, channels);
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsDistortByte(const libmv_CameraIntrinsics *libmvIntrinsics,
|
|
unsigned char *src, unsigned char *dst, int width, int height, float overscan, int channels)
|
|
{
|
|
libmv::CameraIntrinsics *intrinsics = (libmv::CameraIntrinsics *) libmvIntrinsics;
|
|
intrinsics->Distort(src, dst, width, height, overscan, channels);
|
|
}
|
|
|
|
void libmv_CameraIntrinsicsDistortFloat(const libmv_CameraIntrinsics *libmvIntrinsics,
|
|
float *src, float *dst, int width, int height, float overscan, int channels)
|
|
{
|
|
libmv::CameraIntrinsics *intrinsics = (libmv::CameraIntrinsics *) libmvIntrinsics;
|
|
|
|
intrinsics->Distort(src, dst, width, height, overscan, channels);
|
|
}
|
|
|
|
/* ************ utils ************ */
|
|
|
|
void libmv_ApplyCameraIntrinsics(const libmv_cameraIntrinsicsOptions *libmv_camera_intrinsics_options,
|
|
double x, double y, double *x1, double *y1)
|
|
{
|
|
libmv::CameraIntrinsics camera_intrinsics;
|
|
|
|
cameraIntrinsicsFromOptions(libmv_camera_intrinsics_options, &camera_intrinsics);
|
|
|
|
if (libmv_camera_intrinsics_options->focal_length) {
|
|
/* do a lens undistortion if focal length is non-zero only */
|
|
|
|
camera_intrinsics.ApplyIntrinsics(x, y, x1, y1);
|
|
}
|
|
}
|
|
|
|
void libmv_InvertCameraIntrinsics(const libmv_cameraIntrinsicsOptions *libmv_camera_intrinsics_options,
|
|
double x, double y, double *x1, double *y1)
|
|
{
|
|
libmv::CameraIntrinsics camera_intrinsics;
|
|
|
|
cameraIntrinsicsFromOptions(libmv_camera_intrinsics_options, &camera_intrinsics);
|
|
|
|
if (libmv_camera_intrinsics_options->focal_length) {
|
|
/* do a lens distortion if focal length is non-zero only */
|
|
|
|
camera_intrinsics.InvertIntrinsics(x, y, x1, y1);
|
|
}
|
|
}
|
|
|
|
#endif
|