Faster upper body pose recognition and estimation using compute unified device architecture
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Date
2013
Authors
Journal Title
Journal ISSN
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Publisher
University of Western Cape
Abstract
The SASL project is in the process of developing a machine translation system that can
translate fully-fledged phrases between SASL and English in real-time. To-date, several
systems have been developed by the project focusing on facial expression, hand shape,
hand motion, hand orientation and hand location recognition and estimation. Achmed
developed a highly accurate upper body pose recognition and estimation system. The
system is capable of recognizing and estimating the location of the arms from a twodimensional video captured from a monocular view at an accuracy of 88%. The system operates at well below real-time speeds. This research aims to investigate the use of optimizations and parallel processing techniques using the CUDA framework on Achmed’s algorithm to achieve real-time upper body pose recognition and estimation. A detailed analysis of Achmed’s algorithm identified potential improvements to the algorithm. Are- implementation of Achmed’s algorithm on the CUDA framework, coupled with these improvements culminated in an enhanced upper body pose recognition and estimation system that operates in real-time with an increased accuracy.
Description
>Magister Scientiae - MSc
Keywords
Pose recognition and estimation, Graphics processing unit, Compute unified device architecture, Face detection, Skin detection, Background subtraction, Morphological operations, Haar features, Support vector machine, Blender