Journal article
Computing the Cost of Occlusion
Computer vision and image understanding, v 79(2), pp 324-329
Aug 2000
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Recently, Cox et al. (1996, CVGIP: Image Understanding63, 542–567) presented a new dynamic programming-based stereo matching algorithm. The algorithm uses a parameter which represents the cost of occlusion. This cost is levied if the algorithm decides that two measurements, each from a different camera along corresponding epipolar lines, are not projections of the same point in space. The occlusion cost is dependent on the standard deviation of the (Gaussian) sensor noise, σ, and the probability of match detection, PD. Under certain conditions such as low signal-to-noise ratio, the algorithm of Cox et al. will declare occlusions where they do not exist. We offer an alternative definition for the cost of occlusion, based on a decision-theoretic formulation for the matching process. This alternative improves the performance of the matching algorithm.
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Details
- Title
- Computing the Cost of Occlusion
- Creators
- Gabriel Fielding - Drexel UniversityMoshe Kam - Drexel University
- Publication Details
- Computer vision and image understanding, v 79(2), pp 324-329
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000088615800008
- Scopus ID
- 2-s2.0-0034250228
- Other Identifier
- 991019346723404721
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- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic