Dr. Sumeet Dua

Max P. and Robbie L. Watson Eminent Scholar Chair

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Robert W. Clowers (2007)

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A Simplistic Approach to Face Detection over the Access Grid Medium; MS-CS Thesis, Student: Robert W. Clowers (2007).

Access Grid (AG) frameworks are a relatively new medium for enhanced remote instructional delivery, collaborative education, and group learning endeavors.  The declining cost of audio/visual and computing equipment, coupled by the increasing level of interest and support for virtual classrooms, have led to an unprecedented growth of AG nodes in academia and beyond.  While it would be presumptuous to assume that Access Grids are an adequate replacement for classroom teaching, the advances in computing technologies deployed augmented by novel algorithms developed to analyze the AG media holds promise for an enhanced learning experience and subsequently for further functional utilization of the AG capacity.  This thesis has attempted to make a unique contribution in this area of algorithmic technology-driven enriching instructional experience.
We have presented a unique algorithmic framework to model the problem of online feedback from remote attendees as a challenging image processing and mining problem.  A unique face detection algorithm has been proposed with tunable parametric controls to manage the heterogeneity of AG environments.  While a typical AG room will have less than 30 attendees, we have rigorously tested the facial detection accuracy of our algorithm on a variety of complex images leading to an accuracy of 90% in a complex image comprising of 62 faces.  Superior accuracy rates have been achieved for less complex images typically encountered in an AG environment.  The processing time supports a linear progression in proportion to the image size.  While the elucidation of the seamless integration of digital imaging capabilities in live AG environments is far from complete, we believe that this thorough proof-of-principle study will lay the groundwork for future advances in the area of semi-automated facial recognition and attendance management in AG mediums towards more frequent and reliable use of such mediums in the future.

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