Skip to Main content Skip to Navigation
Conference papers

Joint Pose Estimation and Action Recognition in Image Graphs

Kumar Raja 1 Ivan Laptev 2 Patrick Pérez 1 Lionel Oisel 1 
2 WILLOW - Models of visual object recognition and scene understanding
DI-ENS - Département d'informatique - ENS Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
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.
Document type :
Conference papers
Complete list of metadata

Cited literature [14 references]  Display  Hide  Download
Contributor : Suha Kwak Connect in order to contact the contributor
Submitted on : Monday, September 15, 2014 - 3:13:04 PM
Last modification on : Wednesday, April 27, 2022 - 2:09:45 PM
Long-term archiving on: : Tuesday, December 16, 2014 - 10:21:15 AM


Files produced by the author(s)


  • HAL Id : hal-01063329, version 1



Kumar Raja, Ivan Laptev, Patrick Pérez, Lionel Oisel. Joint Pose Estimation and Action Recognition in Image Graphs. IEEE International Conference on Image Processing, Sep 2011, Brussels, Belgium. ⟨hal-01063329⟩



Record views


Files downloads