Adaptive Model for Background Extraction Using Depth Map
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Depth map has attracted great attention for image and video processing in recent years. Depth map gives one more dimensional information about the images besides color (intensity). Depth is independent of color, which is the advantage for extracting the background covered by objects with irregular repetitive motions e.g. rotation. A new algorithm for background extraction using Gaussian Mixture Models (GMM) combined with depth map is presented. The per-pixel mixture model and single Gaussian model are used to model the recent observation in color and depth space respectively. We also incorporate the color-depth consistency check mechanism into the algorithm to improve the accuracy. Our results show much greater robustness than prior state of the art method to handle challenging scenes.
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Jin Z; Tillo T; Zou W; Zhao Y; Li X (Institute of Electrical and Electronics Engineers Inc., 2017)The emerging of depth-camera technology is paving the way for a variety of new applications and it is believed that plane detection is one of them. In fact, planes are common in man-made living structures, thus their ...
Lin C; Zhao Y; Xiao J; Tillo T (Korean Society for Internet Information, 2015)In texture-plus-depth format, depth map compression is an important task. Different from normal texture images, depth maps have less texture information, while contain many homogeneous regions separated by sharp edges. ...