Undergraduate Thesis
Abstract
The following paper develops the theories and methods used in a gesture recognition system implemented as a human-computer interface (HCI). The gesture recognition system recognizes four fundamental static hand gestures and variations for a total of nine gestures. The system uses a variation of the CAMSHIFT algorithm for hand tracking and a minimum distance classifier for classification. The Win32 API is utilized to perform the desired actions, which are determined by a microstate/macrostate architecture by which contextual information is used to correct any falsities in single frame classification. The state oriented model uses order statistics to provide corrections. The software, named MTrack, is implemented using Borland Delphi 7.0 and DirectX and is specifically designed for low-end desktop hardware. E.g. A 600MHz Pentium with commercial off the shelf (COTS) camera hardware.
Thesis | Software Demo | Presentation | Original Webpage