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Carnegie Mellon Robotics Institute

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Abstract

Occlusion boundaries are notoriously difficult for many patch-based computer vision algorithms, but they also provide potentially useful information about scene structure and shape. Using short video clips, we present a novel method for scoring the degree to which edges exhibit occlusion. We first utilize a spatio-temporal edge detector which estimates edge strength, orientation, and normal motion. By then extracting patches from either side of each detected (possibly moving) edglet, we can estimate and compare motion to determine if occlusion is present. This completely local, bottom-up approach is intended to provide powerful low-level information for use by higher-level reasoning methods.

Keywords

occlusion boundaries, edge detection, motion analysis

Notes

Number of pages: 10

Text Reference

Andrew Stein and Martial Hebert, "Local Detection of Occlusion Boundaries in Video," British Machine Vision Conference, September, 2006.

BibTeX Reference

@inproceedings{Stein_2006_5472,
   author = "Andrew Stein and Martial Hebert",
   title = "Local Detection of Occlusion Boundaries in Video",
   booktitle = "British Machine Vision Conference",
   month = "September",
   year = "2006",
}

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