Title :
Structured Light Based Depth Edge Detection for Object Shape Recovery
Author :
Kim, Cheolhwon ; Park, Jiyoung ; Yi, Juneho ; Turk, Matthew
Author_Institution :
Sungkyunkwan University, Korea
Abstract :
This research features a novel approach that efficiently detects depth edges in real world scenes. Depth edges play a very important role in many computer vision problems because they represent object contours. We strategically project structured light and exploit distortion of light pattern in the structured light image along depth discontinuities to reliably detect depth edges. Distortion along depth discontinuities may not occur or be large enough to detect depending on the distance from the camera or projector. For practical application of the proposed approach, we have presented methods that guarantee the occurrence of the distortion along depth discontinuities for a continuous range of object location. Experimental results show that the proposed method accurately detect depth edges of human hand and body shapes as well as general objects.
Keywords :
Biometrics; Cameras; Computer science; Computer vision; Gabor filters; Humans; Image edge detection; Layout; Object detection; Shape;
Conference_Titel :
Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on
Conference_Location :
San Diego, CA, USA
Print_ISBN :
0-7695-2372-2
DOI :
10.1109/CVPR.2005.536