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Recovering human body con .gurations:combining segmentation and recognition
Abstract
The goal of this work is to detect a human figure image and localize his joints and limbs along with their associated pixel masks. In this work we attempt to tackle this problem in a general setting. The dataset we use is a collection of sports news photographs of baseball players, varying dramatically in pose and clothing. The approach that we take is to use segmentation to guide our recognition algorithm to salient bits of the image. We use this segmentation approach to build limb and torso detectors, the outputs of which are assembled into human figures. We present quantitative results on torso localization, in addition to shortlisted full body configurations.
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Citations
Cited by
Articulated pose estimation with flexible mixtures-of-parts
Yang, Y., & Ramanan, D. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995741 · Cited by 990
Articulated Human Detection with Flexible Mixtures of Parts
Yang, Y., & Ramanan, D. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.261 · Cited by 852
Vision-based human motion analysis: An overview
Poppe, R. (2007) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2006.10.016 · Cited by 835
Utility data annotation with Amazon Mechanical Turk
Sorokin, A., & Forsyth, D. (2008) · 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2008.4562953 · Cited by 616
Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation
Tu, Z., & Bai, X. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.186 · Cited by 578
Metadata
- Authors
- Mori, G., Ren, X., Efros, A. A., & Malik, J.
- Venue
- Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.
- Publisher
- IEEE
- Published
- 2004-11-13
- Volume
- 2
- Pages
- 326-333
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2162253476
- Cited by
- 507
- References
- 0
- FWCI
- 23.29
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Mori, G., Ren, X., Efros, A. A., & Malik, J. (2004). Recovering human body con .gurations:combining segmentation and recognition. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. https://doi.org/10.1109/cvpr.2004.1315182
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
