Abstract
We address the problem of scene segmentation and shape recovery from a single real intensity image. Solving this problem is central to obtaining 3-D scene descriptions in realistic applications where perfect data cannot be obtained and only one image is available. The method we propose addresses a large class of generic shapes, namely straight homogeneous generalized cylinders (SHGCs). It consists of the derivation and use of their geometric projective properties in a multi-level grouping approach. We describe an implemented and working system that detects and recovers full SHGC descriptions in the presence of image imperfections such as broken contours, surface markings, shadows and occlusion. We demonstrate our method on complex real images.
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This research was supported by the Advanced Research Projects Agency of the Department of Defense and was monitored by the Air Force Office of Scientific Research under Contract No. F49620-90-C-0078. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon.
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© 1994 Springer-Verlag Berlin Heidelberg
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Zerroug, M., Nevatia, R. (1994). Segmentation and recovery of SHGCs from a real intensity image. In: Eklundh, JO. (eds) Computer Vision — ECCV '94. ECCV 1994. Lecture Notes in Computer Science, vol 800. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57956-7_36
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DOI: https://doi.org/10.1007/3-540-57956-7_36
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