Abstract
Moving object detection is a crucial step in many application contexts such as people detection, action recognition, and visual surveillance for safety and security. The recent advance in depth camera technology has suggested the possibility to exploit a multi-sensor information (color and depth) in order to achieve better results in video segmentation. In this paper, we present a technique that combines depth and color image information and demonstrate its effectiveness through experiments performed on real image sequences recorded by means of a stereo camera.
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References
Piccardi, M.: Background subtraction techniques: a review. Systems, Man and Cybernetics (SMC) 4, 3099–3104
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Computer Vision and Pattern Recognition (CVPR), vol. 2 (1999)
Zivkovic, Z., Van Der Heijden, F.: Recursive unsupervised learning of finite mixture models. IEEE Trans. on Pattern Analysis and Machine Intelligence 26(5) (2004)
Zhu, Z., Wang, Y., Jiang, G.: On multi-view video segmentation for object-based coding. Digital Signal Processing: A Review Journal 22(6), 954–960 (2012)
Cardoso, J.S., Cardoso, J.C.S., Corte-Real, L.: Object-Based Spatial Segmentation of Video Guided by Depth and Motion Information. In: IEEE Workshop on Motion and Video Computing, pp. 7–12 (2007)
Ma, Y., Chen, Q.: Stereo-based object segmentation combining spatio-temporal information. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Chung, R., Hammound, R., Hussain, M., Kar-Han, T., Crawfis, R., Thalmann, D., Kao, D., Avila, L. (eds.) ISVC 2010, Part III. LNCS, vol. 6455, pp. 229–238. Springer, Heidelberg (2010)
Ma, Y., Worrall, S., Kondoz, A.M.: Automatic video object segmentation using depth information and an active contour model. In: IEEE 10th Workshop on Multimedia Signal Processing, pp. 910–914 (2008)
Bleiweiss, A., Werman, M.: Fusing time-of-flight depth and color for real-time segmentation and tracking. In: Kolb, A., Koch, R. (eds.) Dyn3D 2009. LNCS, vol. 5742, pp. 58–69. Springer, Heidelberg (2009)
Mirante, E., Georgiev, M., Gotchev, A.: A fast image segmentation algorithm using color and depth map. In: The True Vision - Capture, Transmission and Display of 3D Video (3DTV), pp. 1–4 (2011)
Crabb, R., Tracey, C., Puranik, A., Davis, J.: Real-time foreground segmentation via range and color imaging. In: Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1–5 (2008)
Dahan, M., Chen, N., Shamir, A., Cohen-Or, D.: Combining color and depth for enhanced image segmentation and retargeting. In: The Visual Computer, pp. 1–13 (2011)
Wang, L., Zhang, C., Yang, R., Zhang, C.: TofCut: Towards Robust Real-time Foreground Extraction Using a Time-of-Flight Camera. In: 3D Data Processing, Visualization and Transmission (3DPVT) (2010)
Salas, J., Tomasi, C.: People detection using color and depth images. In: MartÃnez-Trinidad, J.F., Carrasco-Ochoa, J.A., Ben-Youssef Brants, C., Hancock, E.R. (eds.) MCPR 2011. LNCS, vol. 6718, pp. 127–135. Springer, Heidelberg (2011)
Kawabe, M.: Joo Kooi Tan, Hyoungseop K., Ishikawa, S. and Morie, T.: Extraction of individual pedestrians employing stereo camera images. In: Control, Automation and Systems (ICCAS), pp. 1744–1747 (2011)
Spagnolo, P., Leo, M., D’Orazio, T., Distante, A.: Robust Moving Objects Segmentation by Background Subtraction. In: Image Analysis for Multimedia Interactive Services (WIAMIS), pp. 1744–1747 (2004)
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Ottonelli, S., Spagnolo, P., Mazzeo, P.L., Leo, M. (2013). Foreground Segmentation by Combining Color and Depth Images. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_83
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DOI: https://doi.org/10.1007/978-3-642-38628-2_83
Publisher Name: Springer, Berlin, Heidelberg
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