Switch the detector API to a single function which accepts
a float image and detector options. This makes usage of
feature detection more unified across different algorithms.
Options structure is pretty much straightforward and contains
detector to be used and all the detector-specific settings.
Also implemented Harris feature detection algorithm which
is not as fast as FAST one but is expected to detect more
robust feature points. It is also likely that less features
are detected, but better quality than quantity.
Blender will now use Harris detector by default, later we'll
remove FAST detector.
Summary:
This brings up much easier termination type usage,
which for us means we might use:
ceres::Summary::IsSolutionUsable()
instead of doing manual funky enum values check.
Reviewers: keir
Differential Revision: https://developer.blender.org/D153
- A bit more reasonable name for the estimation option
structure and estimation functions.
- Get rid of unclear function and parameter tolerance,
it wasn't clear at all in which units they are.
Now we've got expected_average_symmetric_distance as
an early output check and as soon as average symmetric
error goes below this threshold refining finishes.
This distance is measured in the same units as input
points are.
It is arguable whether we need callback for this or not,
but seems Ceres doesn't have some kind of absolute
threshold for function value and function_tolerance
behaves different from logic behind expected symmetric
error.
- Added option to normalize correspondences before
estimating the homography in order to increase estimation
stability. See
R. Hartley and A. Zisserman. Multiple View Geometry in Computer
Vision. Cambridge University Press, second edition, 2003.
https://www.cs.ubc.ca/grads/resources/thesis/May09/Dubrofsky_Elan.pdf
Before the refinement phase of tracking, a brute force SAD search
is run across the search area. This works well but is slow;
especially if the guess for the track's location is accurate.
This patch runs a refinement phase before running a brute force
search, hoping that the guessed position (in x2, y2) is close to
the best answer. If it is, then no brute search is done. If it is
not, then a normal brute force search followed by refinement is
done.
In some cases this may produce worse tracks than before; the
regressions will need investigation. The predictive motion model
(to be implemented) will reduce the probability of that happening.
Added a weight slider to track which defines
how much particular track affects in a final
reconstruction. This weight is for sure
animateable.
Currently it affects on BA step only which in
most cases will work just fine.
The usecase of this slider is to have it set
to 1.0 most of the time where the track is
good, but blend it's weight down to 0 when
tracker looses the track. This will prevent
camera from jump.
Tutorial is to be done by Sebastian.
It was rather confusing from the user usage point
of view and didn't get so much improvement after
new bundle adjuster was added.
In the future we might want to switch resection
to PPnP algorithm, which could also might be a
nice alternative to fallback option.
- Tweaked typedefs in stdint so they match
what we've got in BLI_sys_types (needed to
explicitly tell sign to MSVC).
Not so much harmful to be more explicit here,
but we really better to have single stdint
int blender.
- Tweaked allocations macros so MSVC is happy
with structures allocation.
Also made libmv-capi use guarded objetc allocation.
Run into some suspecious cases when it was not so
clear whether memory is being freed or not.
Now we'll know for sure whether there're leaks or not :)
Having this macros in a guardedalloc header helps
using them in other areas (for now it's OCIO and libmv,
but in the future it'll be more places).
Jittering was caused by homography not being estimated
accurate enough.
Before this, only algebraic estimation was used, which
is indeed not so much great, Now use algebraic estimation
followed with refinement step using Ceres minimizer.
The code was already there since keyframe selection patch,
made such estimation a generic function in multiview/ and
changed API for estimation in order to pass all additional
options via an options structure (the same way as it's
done fr Ceres).
This includes changes to both homography and fundamental
estimation.
TODO:
- Need to document Ceres functors better.
- Need to support homogeneous coordinates (currently
only euclidean coords are supported).
This commit includes all the changes made for plane tracker
in tomato branch.
Movie clip editor changes:
- Artist might create a plane track out of multiple point
tracks which belongs to the same track (minimum amount of
point tracks is 4, maximum is not actually limited).
When new plane track is added, it's getting "tracked"
across all point tracks, which makes it stick to the same
plane point tracks belong to.
- After plane track was added, it need to be manually adjusted
in a way it covers feature one might to mask/replace.
General transform tools (G, R, S) or sliding corners with
a mouse could be sued for this. Plane corner which
corresponds to left bottom image corner has got X/Y axis
on it (red is for X axis, green for Y).
- Re-adjusting plane corners makes plane to be "re-tracked"
for the frames sequence between current frame and next
and previous keyframes.
- Kayframes might be removed from the plane, using Shit-X
(Marker Delete) operator. However, currently manual
re-adjustment or "re-track" trigger is needed.
Compositor changes:
- Added new node called Plane Track Deform.
- User selects which plane track to use (for this he need
to select movie clip datablock, object and track names).
- Node gets an image input, which need to be warped into
the plane.
- Node outputs:
* Input image warped into the plane.
* Plane, rasterized to a mask.
Masking changes:
- Mask points might be parented to a plane track, which
makes this point deforming in a way as if it belongs
to the tracked plane.
Some video tutorials are available:
- Coder video: http://www.youtube.com/watch?v=vISEwqNHqe4
- Artist video: https://vimeo.com/71727578
This is mine and Keir's holiday code project :)
Clean up inconsistencies in the libmv C API:
- All type identifiers are libmv_TypeName
- All function identifiers libmv_functionName
- Prefer libmv_nounVerb function names (e.g. libmv_featuresDestroy)
- Match Blender code formatting rather than Google
- Spelling corrections
Code review: https://codereview.appspot.com/11494044/
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.
- Added const modifiers where it makes sense and
helps keep code safe.
- Reshuffled argument to match <inputs>,<outputs>
convention on parameters.
- Pass values to ApplyRadialDistortionCameraIntrinsics
by a constant reference.
This will save lots of CPU ticks passing relatively
heavy jet objects to this function when running
bundle adjustment.
Makes code in tracking.cc much easier to understand and modify,
without worring to breck compulation with Libmv disabled.
It is still possible compilation will break due to libmv-capi
changes, but that's not happening so much often.
