Focused object extraction with multiple cameras

This paper describes a novel framework for object extraction from images utilizing multiple cameras. Focused regions in images and disparities of point correspondences among multiple images are 3-D clues for the extraction. We examine the extraction of focused objects from images by these automatically acquired clues. Edges in images captured by the cameras are detected, and disparities of the edges in focused regions become the clues, called disparity keys. A focused object is extracted from an image as a set of edge intervals with the disparity keys. The falsely extracted parts can be detected by discontinuous contours of the object and recovered by contour morphing. Some experimental results under different conditions demonstrate the effectiveness and robustness of the proposed method. The method can be applied to image synthesis methods, such as synthesis/natural hybrid coding (SNHC) and to object-scalable coding in MPEG-4.