Detecting and Segmenting Un-occluded Items by Actively Casting Shadows

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 th...

• Type: Conference
• Year: 2007
• Where: ACCV
• Authors: Tze Ki Koh, Amit K. Agrawal, Ramesh Raskar, Steve Morgan, Nicholas Miles, Barrie Hayes-Gill
• Keywords: ACCV 2007, Active Illumination Approach, Computer Vision, Practical Approach, Un-occluded Items