Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery

Ronald Walter Poppe, Mannes Poel

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

39 Citations (Scopus)

Abstract

Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations.
Original languageUndefined
Title of host publicationProceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006)
Place of PublicationLos Alamitos
PublisherIEEE Computer Society
Pages541-546
Number of pages6
ISBN (Print)0-7695-2503-2
DOIs
Publication statusPublished - 10 Apr 2006
Event7th International Conference on Automatic Face and Gesture Recognition, FG 2006 - Southhamton, United Kingdom
Duration: 10 Apr 200612 Apr 2006
Conference number: 7
http://www.fg2006.ecs.soton.ac.uk/

Publication series

Name
PublisherIEEE Computer Society Press
Number2

Conference

Conference7th International Conference on Automatic Face and Gesture Recognition, FG 2006
Abbreviated titleFG
CountryUnited Kingdom
CitySouthhamton
Period10/04/0612/04/06
Internet address

Keywords

  • METIS-238153
  • EC Grant Agreement nr.: FP6/506811
  • EWI-6866
  • IR-63418

Cite this

Poppe, R. W., & Poel, M. (2006). Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery. In Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006) (pp. 541-546). [10.1109/FGR.2006.32] Los Alamitos: IEEE Computer Society. https://doi.org/10.1109/FGR.2006.32
Poppe, Ronald Walter ; Poel, Mannes. / Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery. Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006). Los Alamitos : IEEE Computer Society, 2006. pp. 541-546
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abstract = "Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations.",
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Poppe, RW & Poel, M 2006, Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery. in Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006)., 10.1109/FGR.2006.32, IEEE Computer Society, Los Alamitos, pp. 541-546, 7th International Conference on Automatic Face and Gesture Recognition, FG 2006, Southhamton, United Kingdom, 10/04/06. https://doi.org/10.1109/FGR.2006.32

Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery. / Poppe, Ronald Walter; Poel, Mannes.

Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006). Los Alamitos : IEEE Computer Society, 2006. p. 541-546 10.1109/FGR.2006.32.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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N2 - Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations.

AB - Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations.

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Poppe RW, Poel M. Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery. In Proceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006). Los Alamitos: IEEE Computer Society. 2006. p. 541-546. 10.1109/FGR.2006.32 https://doi.org/10.1109/FGR.2006.32