An adaptive coupled-layer visual model for robust visual tracking

This paper addresses the problem of tracking objects which undergo rapid and significant appearance changes. We propose a novel coupled-layer visual model that combines the target’s global and local appearance. The local layer in this model is a set of local patches that geometrically constrain the changes in the target’s appearance. This layer probabilistically adapts to the target’s geometric deformation, while its structure is updated by removing and adding the local patches. The addition of the patches is constrained by the global layer that probabilistically models target’s global visual properties such as color, shape and apparent local motion. The global visual properties are updated during tracking using the stable patches from the local layer. By this coupled constraint paradigm between the adaptation of the global and the local layer, we achieve a more robust tracking through significant appearance changes. Indeed, the experimental results on challenging sequences ...

• Type: Journal
• Year: 2011
• Where: ICCV
• Authors: Luka Cehovin, Matej Kristan, Ales Leonardis
• Keywords: Appearance Changes, Computer Vision, Failure Rate, ICCV 2011, Visual Model