Abstract
In this paper, we present an approach for the segmentation of people silhouettes in images. Since in real-world images estimating pixel probabilities to belong to people or background is difficult, we propose to optimally combine several ones. A local window classifier based on SVMs with Histograms of Oriented Gradients features estimates probabilities from pixels’ appearance. A shape template prior is also computed over a set of training images. From these two probability maps, color distributions relying on color histograms and Gaussian Mixture Models are estimated and the associated probability maps are derived. All these probability maps are optimally combined into a single one with weighting coefficients determined by a genetic algorithm. This final probability map is used within a graph-cut to extract accurately the silhouette. Experimental results are provided on both the INRIA Static Person Dataset and BOSS European project and show the benefit of the approach.
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References
Mori, G., Ren, X., Efros, A.A., Malik, J.: Recovering human body configurations: combining segmentation and recognition. In: Computer Society Conference on Computer Vision and Pattern Recognition, ser. CVPR 2004, pp. 326–333 (2004)
Farenzena, M., Bazzani, L., Perina, A., Murino, V., Cristani, M.: Person re-identification by symmetry-driven accumulation of local features. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2010
Yang, M., Yu, K.: Real-time clothing recognition in surveillance videos. In: ICIP, pp. 2937–2940. IEEE (2011)
Gallagher, A., Chen, T.: Clothing cosegmentation for recognizing people. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8, June 2008
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models forreal-time tracking. In: Computer Vision and Pattern Recognition, vol. 2, pp. 2246–2252 (1999)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: International Conference on Computer Vision & Pattern Recognition, vol. 2, pp. 886–893 (2005)
Zhu, Q., Avidan, S., Yeh, M.-C., Cheng, K.-T.: Fast human detection using a cascade of histograms of oriented gradients. In: CVPR 2006, pp. 1491–1498 (2006)
Gong, S., Cristanio, M., Yan, S., Loy, C.: Person re-identification. Springer (2014)
Jojic, N., Perina, A., Cristani, M., Murino, V., Frey, B.: Stel component analysis: modeling spatial correlations in image class structure. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 2044–2051 (2009)
Migniot, C., Bertolino, P., Chassery, J.-M.: Iterative human segmentation from detection windows using contour segment analysis. In: VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications, pp. 405–412 (2013)
Migniot, C., Bertolino, P., Chassery, J.-M.: Automatic people segmentation with a template-driven graph cut. In: International Conference on Image Processing (2011)
Boss europeen project (on bord wireless secured video surveillance). http://www.multitel.be/image/research-development/research-projects/boss.php
Migniot, C., Bertolino, P., Chassery, J.-M.: Contour segment analysis for human silhouette pre-segmentation. In: 5th International Conference on Computer Vision Theory and Applications (VISAPP 2010), Angers, France, May 2010
Lin, Z., Davis, L.S.: Shape-based human detection and segmentation via hierarchical part-template matching. IEEE Trans. Pattern Anal. Mach. Intell., pp. 604–618 (2010)
Boykov, Y., Jolly, M.: Interactive graph cuts for optimal boundary region segmentation of objects in n-d images. In: IEEE International Conference on Computer Vision, vol. 1, pp. 105–112 (2001)
Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(9), 1124–1137 (2004)
Inria person dataset. http://pascal.inrialpes.fr/data/human/
Sharma, V., Davis, J.: Integrating appearance and motion cues for simultaneous detection and segmentation of pedestrians. In: Computer Vision ICCV IEEE, pp. 1–8. IEEE (2007)
Coniglio, C., Meurie, C., Lzoray, O., Berbineau, M.: A genetically optimized graph-based people extraction method for embedded transportation systems real conditions. In: 17th International Conference on Intelligent Transportation Systems, pp. 1589–1595 (2014)
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Coniglio, C., Meurie, C., Lézoray, O., Berbineau, M. (2015). A Graph Based People Silhouette Segmentation Using Combined Probabilities Extracted from Appearance, Shape Template Prior, and Color Distributions. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_26
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DOI: https://doi.org/10.1007/978-3-319-25903-1_26
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