Paper
7 June 2004 Analysis and synthesis of motion patterns using the projective plane
Cicero Mota, Michael Dorr, Ingo Stuke, Erhardt Barth
Author Affiliations +
Proceedings Volume 5292, Human Vision and Electronic Imaging IX; (2004) https://doi.org/10.1117/12.544552
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
Abstract
We first review theoretical results for the problem of estimating single and multiple transparent motions. For N motions we obtain a M×M generalized structure tensor JN with M = 3 for one, M = 6 for two, and M = 10 for three motions. The analysis of motion patterns is based on the ranks of JN and is thus not only conceptual but provides computable confidence measures for the different types of motions. To resolve the correspondence between the ranks of the tensors and the motion patterns, we introduce the projective plane as a new way of describing motion patterns. In the projective plane, intrinsically 2D spatial patterns (e.g. corners and line ends) that move correspond to points that represent the only admissible velocity, and 1D spatial patterns (e.g. straight edges) that move correspond to lines that represent, as a set of points, the set of admissible velocities. We then show a few examples for how the projective plane can be used to generate novel motion patterns and explain the perception of these patterns. We believe that our results will be useful for designing new stimuli for visual psychophysics and neuroscience and thereby contribute to the understanding of the dynamical properties of human vision.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cicero Mota, Michael Dorr, Ingo Stuke, and Erhardt Barth "Analysis and synthesis of motion patterns using the projective plane", Proc. SPIE 5292, Human Vision and Electronic Imaging IX, (7 June 2004); https://doi.org/10.1117/12.544552
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Motion estimation

Motion analysis

Motion models

Visualization

Superposition

Motion measurement

Biological research

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