>Magister Scientiae - MSc / 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.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uwc/oai:etd.uwc.ac.za:11394/3455 |
| Date | January 2013 |
| Creators | Brown, Dane |
| Contributors | Ghaziasgar, Mehrdad, James Connan, James |
| Publisher | University of Western Cape |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Western Cape |
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