Learning on lie groups for invariant detection and tracking
This paper presents a novel learning based tracking model combined with object detection. The existing techniques proceed by linearizing the motion, which makes an implicit Euclidean space assumption. Most of the transformations used in computer vision have matrix Lie group structure. We learn the motion model on the Lie algebra and show that the formulation minimizes a first order approximation to the geodesic error. The learning model is extended to train a class specific tracking function,...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of CVPR 2008|
|01_Tuzel_Learning_on_lie_groups_for_2008.pdf||3.26 MB||Adobe PDF||Request a copy|
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