International Workshop on Human Activity Understanding from 3D Data (2011)

International Workshop on Human Activity Understanding from 3D Data (HAU3D) 2011, Colorado Springs

Friday, June 24, 2011 

The International Workshop on Human Activity Understanding from 3D Data (HAU3D) 2011 will be held on in conjunction with the IEEE Computer Vision and Pattern Recognition (CVPR) Colorado Springs, June 20-25, 2011


Automatic analysis of human motion has been one of the most active research topics in computer vision due to the scientific challenges of the problem and the wide range of applications. Such applications include intelligent video surveillance, human-computer-interface (HCI), intelligent humanoid robots, diagnosis, assessment and treatment of musculoskeletal disorders, sports analysis, realistic synthesis and animation of human motion, and monitoring of elderly and disabled people at home. Extensive study has been conducted in the past decade using 2D visual information captured by single or multiple cameras. However, the problem, especially robust and viewpoint independent recognition of the diverse human actions and activities in a real environment is far from being solved.

Recent advances in 3D depth cameras using structured light or time-of-flight sensors, 3D information recovery from 2D images/videos, and the availability of portable human motion capture devices have been nurturing a potential breakthrough solution to the problem of human activity recognition by using 3D data. The announcement of Microsoft Project Natal for Xbox 360 in 2009 together with its recent demonstration of Kinect games at Japan Expo 2010, and the introduction of 3D webcam by Promotion and Display Technology Ltd. UK have demonstrated that capturing real-time 3D data is becoming feasible and commercially viable.


This workshop is to bring together leading researchers in the related fields of 3D data capture, representation and invariant description of 3D data, human motion modeling and applications of human motion analysis in order to advocate and promote research in human activity recognition using 3D data. The workshop aims to provide an interactive forum for researchers to disseminate their most recent research results, rigorously and systematically discuss potential solutions and challenges towards a robust human activity recognition using 3D data, and to promote new collaborations amongst the researchers.


  • Michael Black, Brown University, USA
  • David Hogg, University of Leeds, UK
  • Zhengyou Zhang, Microsoft Research, USA