3D Pose Tracking Using Optical Flow
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Issue Date
2010-08-30
Language
en
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Abstract
An action recognition system has many applications, ranging from security to sign language interpretation. If a subject's body pose can be tracked in streams of video, a wealth of information
about possible actions can be extracted. In this thesis a three dimensional pose tracking system is
presented, designed so that its output can be used as input for an action recognition system. By
presenting a classifier with optical
flow and low resolution greyscale images, the system is able to
detect and track a subject's pose over an extended period of time. Optical
flow is the distribution
of motion over an image, and was hypothesized to be an important factor in the system's ability
to perceive depth. Investigations into the effect of optical
flow reveal it to be important for the
system's performance, yet less important than other inputs when it comes to depth perception.
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Faculteit der Sociale Wetenschappen