Combining Motion And Segmentation Information For Localization Of Occlusion Boundaries

Keith Moler; Alan Scherf

doi:10.1117/12.948477

16 December 1988 Combining Motion And Segmentation Information For Localization Of Occlusion Boundaries

Keith Moler, Alan Scherf

Proceedings Volume 0974, Applications of Digital Image Processing XI; (1988) https://doi.org/10.1117/12.948477
Event: 32nd Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1988, San Diego, CA, United States

Abstract

An algorithm is presented for the accurate detection of occlusion boundaries in an image sequence. Both segmentation and optical flow information is utilized to form a motion image. This fusion process employs an assumption of optical flow continuity within each segmentation region. Continuity is not assumed between segmentation regions, thereby preserving potential occlusion boundaries. Two approaches for the detection of occlusion boundaries in this motion image are presented and compared. The first is the Marr-Hildreth edge detector and the second applies cluster analysis and linear modeling techniques. The algorithm has been tested on infrared imagery, and occlusion boundaries have been detected with a high degree of localization accuracy.

Citation Download Citation

Keith Moler and Alan Scherf "Combining Motion And Segmentation Information For Localization Of Occlusion Boundaries", Proc. SPIE 0974, Applications of Digital Image Processing XI, (16 December 1988); https://doi.org/10.1117/12.948477

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