- Adding OpenCV and OpenMVG as GIT submodules to the project
- It allows local compilation and debug
- Changes to main repositories can be submitted as contributions
- Porting Essential matrix estimation and decomposition to OpenCV
- Both algorithms are now implemented in 3.0 version
- OpenCV seems up to twice times faster thanks to OpenCL support
- Analyzing implementations of stereo matching algorithms
- Dense depth map for current frame
$I_i$ is fused with$I_{0..i-1}$ in a cost volume, according to @newcombe2010dtam - PathMatch stereo algorithm from @bleyer2011patchmatch
- Dense depth map for current frame
- Implemented support for block matching in GPU using OpenCV CUDA support
- Added a basic point cloud rendering shader to represent depths from disparity maps using
cv::cuda::reprojectTo3D()
- Added a basic point cloud rendering shader to represent depths from disparity maps using
- Added visualization using OpenGL avoiding to download the image from GPU
- Refactored rendering code to use a "layer" drawing concept in OpenGL
- Created a Layer to render OpenCV images coming from CPU / GPU
- Studying and documenting a general framework to feedback reconstruction and recognition (see
rec2rec.mdfor more information) - Recorded a video demoing the camera tracking using the OpenCV essential estimator
- Documentation:
- Added more documentation related with fibrations and fiber bundles
- Improved description of relations between Lie groups and Lie algebras
- Added total variation description as the regularization term in optimization approaches
- Added explanation of linearization of the
$GL$ group using a structural group
- Added explanation of linearization of the
- Implementation and code review:
- Analysis of the Urho3D project as a C++ rendering engine for future AR applications
- Study JNI bridge for executing native ARM code from Java applications in Android
- Reading optimization procedures in the
$\mathfrak{SE}(3)$ algebra instead in the$SE(3)$ group