Motion capture and classification (MC2) are important tasks in fields such as sports sciences, biometrics, and particularly in computer animation, medicine and surveillance systems, where large collections of motion material are archived and processed. In recent years, the gaming industry has done extensive research in motion detection and processing, resulting in low-cost and yet effective systems. However, there are many new applications that require specific and customised motion capture and classification capability, necessitating further research into these areas.

Topics of interest that MC2 covers include general motion capture and classification techniques and methodologies, as well as their novel applications (but are not limited to):

  • surveillance systems: motion detection, classification, tracking
  • understanding and description of human behaviours
  • human identification, occlusion handling
  • gesture recognition
  • classification of 3D gait analysis data
  • motion sensing techniques
  • motion sensing devices: Kinect / Wii sensors
  • human motion/action recognition
  • models for articulated objects: joint detection and pose estimation
  • e-learning systems based on motion capture
  • collaborative motion capture and classification
  • motion recognition in assistive technologies
  • real-time motion tracking and classification systems
  • motion classification techniques
  • motion capture and classification applications
  • motion capture and classification in networking
  • 3D animation and simulation-based training systems
  • rigid body motion – robot motion
  • similarity, retrieval and classification of motion data


Extended version of selected papers will be considered for publication in several international journals.