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Better appearance models for pictorial structures
Open accessAbstract
We present a novel approach for estimating body part appearance models for pictorial structures. We learn latent relationships between the appearance of different body parts from annotated images, which then help in estimating better appearance models on novel images. The learned appearance models are general, in that they can be plugged into any pictorial structure engine. In a comprehensive evaluation we demonstrate the bene?ts brought by the new appearance models to an existing articulated human pose estimation algorithm, on hundreds of highly challenging images from the TV series Buffy the vampire slayer and the PASCAL VOC 2008 challenge.
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Cited by
Efficient object localization using Convolutional Networks
Tompson, J., Goroshin, R., Jain, A., LeCun, Y., & Bregler, C. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298664 · Cited by 1,365
Towards Viewpoint Invariant 3D Human Pose Estimation
Haque, A., Peng, B., Luo, Z., Alahi, A., Yeung, S., & Fei-Fei, L. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46448-0_10 · Cited by 169
MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation
Jain, A., Tompson, J., LeCun, Y., & Bregler, C. (2015) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-16808-1_21 · Cited by 142
Metadata
- Authors
- Eichner, M., & Ferrari, V.
- Venue
- Procedings of the British Machine Vision Conference 2009
- Publisher
- British Machine Vision Association
- Published
- 2009
- Pages
- 3.1-3.11
- OpenAlex
- W2009647132
- Cited by
- 219
- References
- 0
- FWCI
- 16.90
- Type
- conference paper
- Language
- en
- Open access
- green
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