System for automatically posing 3D models from 2D images.
- OpenCV (>2.4.2)
- Assimp SDK
- Freeglut
- ASSIMP_INCLUDE: assimp\assimp--3.0.1270-sdk\include;C:\Programming\assimp\assimp--3.0.1270-sdk\lib\assimp_debug-dll_win32;C:\Programming\assimp\assimp--3.0.1270-sdk\lib\assimp_debug-dll_x64;C:\Programming\assimp\assimp--3.0.1270-sdk\lib\assimp_release-dll_win32;C:\Programming\assimp\assimp--3.0.1270-sdk\lib\assimp_release-dll_x64
- FREEGLUT: freeglut\
- opencv\opencv2-4-6\
- Loading of 3D models.
- Loading of skeletons.
- Animation (joint manipulation, joint constraints).
- Silhouette descriptor.
- Joint descriptor.
- Distance metrics.
- PSO implementation.
- Overall structure of the project.
- OpenGL rendering.
- Separation of fitness function from main meta-heuristic algorithm.
- Seperation of update functions for particles for further experimentation.
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- KD-tree? Either to limit the search space, but also for combination with database.
- Different meta-heuristics?
- Different descriptors? Silhouette, edge, joint... what else? (e.g. DCT better than HLAC and other nonlinear methods)
- Additional user input (e.g. relative depths between joints)
- IK initialisation
- What happens with multiple frames if temporal data exists?
- GrabCut to segment character from background?
- First go through past papers where they do it with video
- Then show how some other metrics/descriptors actually improve performance
- Transfer this to the drawing problem rather than video
- Show how you can estimate the 3D pose similarly
- From optimisation go to database
- Show how database can work and what results it brings
- Show how it can be linked with the optimisation approach
- Unified system