TY - GEN
T1 - Detecting and segmenting un-occluded items by actively casting shadows
AU - Koh, Tze K.
AU - Agrawal, Amit
AU - Raskar, Ramesh
AU - Morgan, Steve
AU - Miles, Nicholas
AU - Hayes-Gill, Barrie
PY - 2007
Y1 - 2007
N2 - We present a simple and practical approach for segmenting un-occluded items in a scene by actively casting shadows. By 'items', we refer to objects (or part of objects) enclosed by depth edges. Our approach utilizes the fact that under varying illumination, un-occluded items will cast shadows on occluded items or background, but will not be shadowed themselves. We employ an active illumination approach by taking multiple images under different illumination directions, with illumination source close to the camera. Our approach ignores the texture edges in the scene and uses only the shadow and silhouette information to determine the occlusions. We show that such a segmentation does not require the estimation of a depth map or 3D information, which can be cumbersome, expensive and often fails due to the lack of texture and presence of specular objects in the scene. Our approach can handle complex scenes with self-shadows and specularities. Results on several real scenes along with the analysis of failure cases are presented.
AB - We present a simple and practical approach for segmenting un-occluded items in a scene by actively casting shadows. By 'items', we refer to objects (or part of objects) enclosed by depth edges. Our approach utilizes the fact that under varying illumination, un-occluded items will cast shadows on occluded items or background, but will not be shadowed themselves. We employ an active illumination approach by taking multiple images under different illumination directions, with illumination source close to the camera. Our approach ignores the texture edges in the scene and uses only the shadow and silhouette information to determine the occlusions. We show that such a segmentation does not require the estimation of a depth map or 3D information, which can be cumbersome, expensive and often fails due to the lack of texture and presence of specular objects in the scene. Our approach can handle complex scenes with self-shadows and specularities. Results on several real scenes along with the analysis of failure cases are presented.
UR - http://www.scopus.com/inward/record.url?scp=38149043517&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-76386-4_90
DO - 10.1007/978-3-540-76386-4_90
M3 - Conference contribution
AN - SCOPUS:38149043517
SN - 9783540763857
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 945
EP - 955
BT - Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings
PB - Springer Verlag
T2 - 8th Asian Conference on Computer Vision, ACCV 2007
Y2 - 18 November 2007 through 22 November 2007
ER -