Discrimination thresholds for channel-coded systems
Biological Cybernetics
Spatiotemporally Adaptive Estimation and Segmenation of OF-Fields
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
AFPAC '00 Proceedings of the Second International Workshop on Algebraic Frames for the Perception-Action Cycle
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
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Junctions play an important role in motion analysis. Approaches based on the structure tensor have become the standard for junction detection. However, the structure tensor is not able to classify junctions into different types (L, T, Y, X etc.).We propose to solve this problem by the wedge channel representation. It is based on the same computational steps as used for the (anisotropic) structure tensor, but stores results into channel vectors rather than tensors. Due to one-sided channel smoothing, these channel vectors not only represent edge orientation (as existing channel approaches do) but edge direction. Thus junctions cannot only be detected, but also fully characterized.