University of Twente Student Theses


Body pose tracking in the Watching Window : a system that tracks both hands in a virtual reality environment

Herms, K.G.F. (2007) Body pose tracking in the Watching Window : a system that tracks both hands in a virtual reality environment.

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Abstract:This thesis is written for the closure of the master course Human Media Interaction at the University of Twente. This thesis describes a research project related to the Watching Window (WW) project of the University of Otago. The WW is a Virtual Reality (VR) environment in which the user can interact with a VR application without the use of body suits, markers or gloves. To achieve this interaction, the user's head is tracked by several cameras and these head coordination's are triangulated to estimate the coordination in 3D world space. With this 3D coordination, the right perspective of a VR application is drawn by a projector on a screen. This enables the user to see the 3D scenery in the right perspective continually, giving the user the right motion parallax while the user moves around. With the help of some stereo glasses, the user can even experience a 3D effect. The current applications only use the motion parallax and 3D effect while more interesting and challenging applications are possible if the user can physically interact with the VR world. This thesis describes a system that tracks both hands of the user making more interaction with the VR world possible. A hand-tracking module is presented that uses all available cameras to estimate the current upper body pose of the user. Both hands are derived from the estimated pose and used in the WW applications. The body pose estimation technique used in the module is based on a model based pose estimation technique and a particle filter is used to track the body pose of the user. A 3D model is used that can be projected on every camera observation making a generic evaluation possible. This enables the use of all possible cameras for the evaluation which makes more information available and solves camera observation ambiguity. The dimensionality of the model is reduced by decomposing the model into separate body-part estimation problems. Each of these body part estimation problems is solved by a model based particle filter. The hand-tracking module is evaluated by 2 evaluation tests namely an accuracy and a performance evaluation test. From these evaluation tests it can be concluded that the hand-tracking module proposed in this thesis, works well enough for pointing and manipulating objects. However, for detailed hand tracking and small movement the method described in this thesis is not sufficient. Some future work proposes the redesign of the image feature, the projection of the particles and an addition to the model to enable more detailed tracking.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Interaction Technology MSc (60030)
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