Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiview Constraints on Homographies
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
The Rank 4 Constraint in Multiple (=3) View Geometry
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Multi-View Subspace Constraints on Homographies
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
3D SSD Tracking with Estimated 3D Planes
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Implicit Feedback between Reconstruction and Tracking in a Combined Optimization Approach
Proceedings of the 30th DAGM symposium on Pattern Recognition
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Typical tracking algorithms exploit temporal coherence, in the sense of expecting only small object motions. Even without exact knowledge of the scene, additional spatial coherence can be exploited by expecting only a rigid 3d motion. Feature tracking will benefit from knowing about this rigidity of the scene, especially if individual features cannot be tracked by themselves due to occlusions or illumination changes. We present and compare different approaches of dealing with the spatial coherence in the context of tracking planar scenes. We also show the benefits in scenes with occlusions and changes in illumination, even without models of these distortions.