Abstract
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.
B. Sun—This work was supported by National Natural Science Foundation of China (No. 61210006, No. 60972085).
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Sun, B., Tillo, T., Xu, M. (2015). Adaptive Model for Background Extraction Using Depth Map. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9315. Springer, Cham. https://doi.org/10.1007/978-3-319-24078-7_42
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DOI: https://doi.org/10.1007/978-3-319-24078-7_42
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