In this paper, we propose an accurate and robust video segmentation method. The main contributions are threefold: (1) multiple cues (appearance and shape) are explicitly used and adaptively combined to determine segment probability; (2) motion is implicitly used to compute the shape cue; and (3) the segment labeling is improved by utilizing geodesic graph cuts. Experimental results show the effectiveness of the proposed method.
Woo-sung Shim, Se-hoon Kim, Soochahn Lee, "Adaptive Combination of Local Motion, Appearance, and Shape for Video Segmentation" in Journal of Imaging Science and Technology, 2016, https://doi.org/10.2352/J.ImagingSci.Technol.2016.60.6.060409