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Strong Appearance and Expressive Spatial Models for Human Pose Estimation


Conference Paper


Typical approaches to articulated pose estimation combine spatial modelling of the human body with appearance modelling of body parts. This paper aims to push the state-of-the-art in articulated pose estimation in two ways. First we explore various types of appearance representations aiming to substantially improve the body part hypotheses. And second, we draw on and combine several recently proposed powerful ideas such as more flexible spatial models as well as image-conditioned spatial models. In a series of experiments we draw several important conclusions: (1) we show that the proposed appearance representations are complementary; (2) we demonstrate that even a basic tree-structure spatial human body model achieves state-of-the-art performance when augmented with the proper appearance representation; and (3) we show that the combination of the best performing appearance model with a flexible image-conditioned spatial model achieves the best result, significantly improving over the state of the art, on the "Leeds Sports Poses'' and "Parse'' benchmarks.

Author(s): Leonid Pishchulin and Micha Andriluka and Peter Gehler and Bernt Schiele
Book Title: International Conference on Computer Vision (ICCV)
Pages: 3487 - 3494
Year: 2013
Month: December
Publisher: IEEE

Department(s): Perceiving Systems
Research Project(s): 2D Pose from Images
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

DOI: 10.1109/ICCV.2013.433
Event Name: Computer Vision (ICCV), 2013 IEEE International Conference on
Event Place: Sydney, NSW
Attachments: pdf


  title = {Strong Appearance and Expressive Spatial Models for Human Pose Estimation},
  author = {Pishchulin, Leonid and Andriluka, Micha and Gehler, Peter and Schiele, Bernt},
  booktitle = {International Conference on Computer Vision (ICCV)},
  pages = {3487 - 3494 },
  publisher = {IEEE},
  month = dec,
  year = {2013},
  month_numeric = {12}