CS7322: Computer Vision II: Final Project Proposal
Image Stabilization of Video
Gabriel J. Brostow
The Idea:
In order to allow image differencing and object tracking vision algorithms
to function in real-world situations, video data must be preprocessed to
remove the effects of camera/cameraperson movement. In essence, an automated
system can be developed which will be able to distinguish the difference
between objects in the scene moving, and the camera itself moving. As humans,
we do this rather easily.
The Domain and the Scope:
I will process data captured with a hand-held camera in both indoor and
outdoor settings. At the least, I will identify translational motion of
the camera relative to the objects in the scene, assuming at least half
of the scene is actually static. Hopefully, I will be able to also compensate
for camera rotations, zooms, and for scenes where the majority of the image
is changing due to objects moving.
Approach:
I have already found several research papers which explore the two most
common methods for image stabilization: methods based on optical flow,
and methods based on feature tracking. Both methods have been used successfully,
but both have drawbacks. Optical flow robustness decreases as the number
of moving objects increases. Feature tracking can misidentify the desired
feature and result in grossly scewed motion compensations. This method
is also especially susceptible to errors caused by occlusions.
Proposed Time-line:
Week 1:
Finish reading previous work.
Week 2:
Perform evaluation
of existing packages and algorithms to find out previous sucesses and failures
in
real systems.
Week 3+:
Desing
and implement my own system in C/C++.
Final: Incorporate into other vision systems as a preprocessing
stage.