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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Raja, K. Laptev, I. Perez, P. Oisel, L. |
| Copyright Year | 2011 |
| Description | Author affiliation: INRIA - Willow Project, Laboratoire d´Informatique, École Normale Supérieure, France (Laptev, I.) || Technicolor Research and Innovation, Cesson-Sévigné, France (Raja, K.; Perez, P.; Oisel, L.) |
| Abstract | Human analysis in images and video is a hard problem due to the large variation in human pose, clothing, camera view-points, lighting and other factors. While the explicit modeling of this variability is difficult, the huge amount of available person images motivates for the implicit, data-driven approach to human analysis. In this work we aim to explore this approach using the large amount of images spanning a subspace of human appearance. We model this subspace by connecting images into a graph and propagating information through such a graph using a discriminatively-trained graphical model. We particularly address the problems of human pose estimation and action recognition and demonstrate how image graphs help solving these problems jointly. We report results on still images with human actions from the KTH dataset. |
| Starting Page | 25 |
| Ending Page | 28 |
| File Size | 438623 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781457713040 |
| ISSN | 15224880 |
| e-ISBN | 9781457713033 |
| e-ISBN | 9781457713026 |
| DOI | 10.1109/ICIP.2011.6116197 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-09-11 |
| Publisher Place | Belgium |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Humans Image recognition Estimation Joints Graphical models Training Conferences Graph optimization Action Recognition in still images Pose estimation |
| Content Type | Text |
| Resource Type | Article |
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