2D articulated human pose estimation software v1.05
Marcin Eichner, Manuel J. Marín-Jiménez, Andrew Zisserman, Vittorio Ferrari
Perona November 2009 Challenge
Here we show results from the Perona November 2009 challenge. The original images can be downloaded from here.
We show below all images in the challenge, which have been collected independently from Pietro Perona and his group at Caltech to test the limits of our technique. For each image we show all detected upper-bodies and all pose estimates. What you see here is exactly all the output of the two packages you can download from this website (i.e. the upper-body detector and the pose estimator).
We present one image per row. The first column shows all detections. Each remaining column shows the pose estimated for a different detection.
Click on an image to enlarge it.
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Return to the software page
Related Publications
[1] Ferrari, V., Marin-Jimenez, M. and Zisserman, A.
Progressive Search Space Reduction for Human Pose Estimation
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2008)
Bibtex source
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Abstract
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Document: ps.gz PDF
[2] Ferrari, V. and Marin-Jimenez, M. and Zisserman, A.
2D Human Pose Estimation in TV Shows
Proceedings of the Dagstuhl Seminar on Stastistical and Geometrical Approaches to Visual Motion Analysis, 2009.
Document: PDF
[3] Ferrari, V., Marin-Jimenez, M. and Zisserman, A.
Pose search: retrieving people using their pose
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2009)
Bibtex source
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Abstract
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Document: ps.gz PDF
[4] Eichner, M. and Ferrari, V.
Better Appearance Models for Pictorial Structures
Proceedings of British Machine Vision Conference (BMVC), 2009.
Document: PDF
Acknowledgements
We would like to thank Deva Ramanan, Varun Gulshan, Pushmeet Kohli and Vladimir Kolmogorov, who contributed to this code release.
This work is funded by the EU Project CLASS, the Swiss National Science Foundation SNSF and the Spanish Ministry of Education and Science (under FPU grant) and ERC Project VisRec
