Free viewpoint action recognition using motion history volumes

Daniel Weinland (1) , Rémi Ronfard (1) , Edmond Boyer (1)

1 PERCEPTION - Interpretation and Modelling of Images and Videos

Action recognition is an important and challenging topic in computer vision, with many important applications including video surveillance, automated cinematography and understanding of social interaction. Yet, most current work in gesture or action interpretation remains rooted in view-dependent representations. This paper introduces Motion History Volumes (MHV) as a free-viewpoint representation for human actions in the case of multiple calibrated, and background-subtracted, video cameras. We present algorithms for computing, aligning and comparing MHVs of different actions performed by different people in a variety of viewpoints. Alignment and comparisons are performed efficiently using Fourier transforms in cylindrical coordinates around the vertical axis. Results indicate that this representation can be used to learn and recognize basic human action classes, independently of gender, body size and viewpoint.

Mots clés: action recognition; view invariance; volumetric reconstruction

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Daniel Weinland, Rémi Ronfard, Edmond Boyer. Free viewpoint action recognition using motion history volumes. Computer Vision and Image Understanding, 2006, 104 (2-3), pp.249-257. ⟨10.1016/j.cviu.2006.07.013⟩. ⟨inria-00544629⟩