Abstract
Clothing segmentation is a challenging field of research which is rapidly gaining attention. This paper presents a system for semantic segmentation of primarily monochromatic clothing and printed/stitched textures in single images or live video. This is especially appealing to emerging augmented reality applications such as retexturing sports players’ shirts with localized adverts or statistics in TV/internet broadcasting. We initialise points on the upper body clothing by body fiducials rather than by applying distance metrics to a detected face. This helps prevent segmentation of the skin rather than clothing. We take advantage of hue and intensity histograms incorporating spatial priors to develop an efficient segmentation method. Evaluated against ground truth on a dataset of 100 people, mostly in groups, the accuracy has an average F-score of 0.97 with an approach which can be over 88% more efficient than the state of the art.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cushen, G., Nixon, M.: Markerless Real-Time garment retexturing from monocular 3D reconstruction. In: IEEE ICSIPA, Malaysia, pp. 88–93 (2011)
Sivic, J., Zitnick, C.L., Szeliski, R.: Finding people in repeated shots of the same scene. In: BMVC, vol. 3, pp. 909–918 (2006)
Gallagher, A.C., Chen, T.: Clothing cosegmentation for recognizing people. In: CVPR 2008, pp. 1–8. IEEE (2008)
Lee, M.W., Cohen, I.: A model-based approach for estimating human 3D poses in static images. IEEE TPAMI, 905–916 (2006)
Schnitman, Y., Caspi, Y., Cohen-Or, D., Lischinski, D.: Inducing Semantic Segmentation from an Example. In: Narayanan, P.J., Nayar, S.K., Shum, H.-Y. (eds.) ACCV 2006. LNCS, vol. 3852, pp. 373–384. Springer, Heidelberg (2006)
Hu, Z., Yan, H., Lin, X.: Clothing segmentation using foreground and background estimation based on the constrained Delaunay triangulation. Pattern Recognition 41, 1581–1592 (2008)
Hasan, B., Hogg, D.: Segmentation using Deformable Spatial Priors with Application to Clothing. In: BMVC, pp. 1–11 (2010)
Wang, N., Ai, H.: Who Blocks Who: Simultaneous Clothing Segmentation for Grouping Images. In: ICCV (2011)
Yang, M., Yu, K.: Real-time clothing recognition in surveillance videos. In: IEEE ICIP, pp. 2937–2940 (2011)
Seely, R.D., Samangooei, S., Lee, M., Carter, J.N., Nixon, M.S.: The University of Southampton Multi-Biometric Tunnel and introducing a novel 3D gait dataset. In: BTAS, pp. 1–6. IEEE (2008)
Gallagher, A., Chen, T.: Understanding Images of Groups Of People. In: CVPR (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cushen, G.A., Nixon, M.S. (2012). Real-Time Semantic Clothing Segmentation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33179-4_27
Download citation
DOI: https://doi.org/10.1007/978-3-642-33179-4_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33178-7
Online ISBN: 978-3-642-33179-4
eBook Packages: Computer ScienceComputer Science (R0)