Bilayer Segmentation of Webcam Videos Using Tree-Based Classifiers

—This paper presents an automatic segmentation algorithm for video frames captured by a (monocular) webcam that closely approximates depth segmentation from a stereo camera. The frames are segmented into foreground and background layers that comprise a subject (participant) and other objects and individuals. The algorithm produces correct segmentations even in the presence of large background motion with a nearly stationary foreground. This research makes three key contributions: First, we introduce a novel motion representation, referred to as “motons,” inspired by research in object recognition. Second, we propose estimating the segmentation likelihood from the spatial context of motion. The estimation is efficiently learned by random forests. Third, we introduce a general taxonomy of tree-based classifiers that facilitates both theoretical and experimental comparisons of several known classification algorithms and generates new ones. In our bilayer segmentation algorithm, dive...

• Type: Journal
• Year: 2011
• Where: PAMI
• Authors: Pei Yin, Antonio Criminisi, John M. Winn, Irfan A. Essa
• Keywords: Algorithm, Automatic Segmentation Algorithm, Depth Segmentation, Operations Research, PAMI 2011