Kinectavatar: Fully Automatic Body Capture Using a Single Kinect

Kinectavatar: Fully Automatic Body Capture Using a Single Kinect
Yan Cui, Will Chang, Tobias Nöll, Didier Stricker
ACCV Workshop on Color Depth Fusion in Computer Vision 2012 Workshop on Color Depth Fusion in Computer Vision (ACCV-12), November 5-9, Daejeon, Korea, Republic of

Abstract:: We present a novel scanning system for capturing a full 3D human body model using just a single depth camera and no auxiliary equipment. We claim that data captured from a single Kinect is sufficient to produce a good quality full 3D human model. In this setting, the challenges we face are the sensor’s low resolution with random noise and the subject’s non-rigid movement when capturing the data. To overcome these challenges, we develop an improved superresolution algorithm that takes color constraints into account. We then align the super-resolved scans using a combination of automatic rigid and non-rigid registration. As the system is of low price and obtains impressive results in several minutes, full 3D human body scanning technology can now become more accessible to everyday users at home.

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Kinectavatar: Fully Automatic Body Capture Using a Single Kinect

Abstract:: We present a novel scanning system for capturing a full 3D human body model using just a single depth camera and no auxiliary equipment. We claim that data captured from a single Kinect is sufficient to produce a good quality full 3D human model. In this setting, the challenges we face are the sensor’s low resolution with random noise and the subject’s non-rigid movement when capturing the data. To overcome these challenges, we develop an improved superresolution algorithm that takes color constraints into account. We then align the super-resolved scans using a combination of automatic rigid and non-rigid registration. As the system is of low price and obtains impressive results in several minutes, full 3D human body scanning technology can now become more accessible to everyday users at home.

Back to the overview