TY - GEN
T1 - Structured light based depth edge detection for object shape recovery
AU - Kim, Cheolhwon
AU - Park, Jiyoung
AU - Yi, Juneho
AU - Turk, Matthew
N1 - Publisher Copyright:
© 2005 IEEE Computer Society. All rights reserved.
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/70350055832
U2 - 10.1109/CVPR.2005.536
DO - 10.1109/CVPR.2005.536
M3 - Conference contribution
AN - SCOPUS:70350055832
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
BT - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
PB - IEEE Computer Society
T2 - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
Y2 - 21 September 2005 through 23 September 2005
ER -