Articulated body pose estimation: Difference between revisions
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Articulated Body [[Pose]] Estimation in [[Computer Vision]] is a study of algorithms and systems to recover the pose of an articulated body which consists of joints and rigid parts using image-based observations. It is one of the most enduring problems in Computer Vision because of the complexity of the models which relate observation with pose, and because of the variety of situations in which such a device would be useful.<ref>[http://citeseer.ist.psu.edu/moeslund01survey.html Survey of Computer Vision-Based Human Motion Capture (2001)]</ref><ref>[http://www.sciencedirect.com/science/article/B6WCX-4M1DB7H-1/2/8da6f6e7a8c8e07d9331bc7738c6d499 Survey of Advances in Computer Vision-based Human Motion Capture (2006)]</ref> |
Articulated Body [[Pose]] Estimation in [[Computer Vision]] is a study of algorithms and systems to recover the pose of an articulated body which consists of joints and rigid parts using image-based observations. It is one of the most enduring problems in Computer Vision because of the complexity of the models which relate observation with pose, and because of the variety of situations in which such a device would be useful.<ref>[http://citeseer.ist.psu.edu/moeslund01survey.html Survey of Computer Vision-Based Human Motion Capture (2001)]</ref><ref>[http://www.sciencedirect.com/science/article/B6WCX-4M1DB7H-1/2/8da6f6e7a8c8e07d9331bc7738c6d499 Survey of Advances in Computer Vision-based Human Motion Capture (2006)]</ref> |
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Revision as of 23:06, 15 September 2007
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Articulated Body Pose Estimation in Computer Vision is a study of algorithms and systems to recover the pose of an articulated body which consists of joints and rigid parts using image-based observations. It is one of the most enduring problems in Computer Vision because of the complexity of the models which relate observation with pose, and because of the variety of situations in which such a device would be useful.[1][2]
A commercially successful but specialized computer vision-based articulated body pose estimation techniques is optical motion capture. This approach involves placing markers on the individual at strategic locations to capture the 6 degrees-of-freedom pose of each body part.
The desire to develop accurate tether-less, vision-based articulated body pose estimation systems. These bodies may be the human body, hand, or even other creatures. Such a system have several foreseeable applications, including marker-less motion capture for human-computer interfaces, physiotherapy, 3D animation, ergonomics studies, robot control and surveillance. One of the major difficulties in recovering pose from images is the high number of degrees-of-freedom (DOF) in movement that needs to be recovered. Any rigid object requires 6 DOF to fully describe its pose. Each additional rigid object connected to it adds at least 1 DOF. A human body contains no less than 10 large body parts, equating to more than 20 DOFs. The difficulty is compounded by with the problem of self-occlusion, where body parts occlude each other depending on the configuration. Other challenges involve dealing with varying illumination which affect appearance,varying subject attire or body type, required camera configuration, required computation time.
Promises in Applications
- Driver body pose estimation for inferring driver intent
- Smart meeting rooms
- Human Computer Interfaces
- Human Activity Recognition
Types of Observations
- Visible wavelength imagery
- Long-wave thermal infrared imagery
- Time-of-flight imagery
- Laser range scanner imagery
Active Research Groups
A number of groups are actively pursuing this topic.