The current project presents the development of R-Eye, a face detection and tracking system implemented as an embedded device based on the Arduino microcontroller. The system is programmed in Python using the Viola-Jones algorithm for image processing. Several experiments designed to measure and compare the performance of the system under various conditions show that the system performs well when used with an integrated camera, reaching a 93% face recognition accuracy for a clear face. The accuracy is lower when detecting a face with accessories, such as a pair of eyeglasses (80%), or when a low-resolution low-quality camera is used. Experimental results also show that the system is capable of detecting and tracking a face within a frame containing multiple faces.
|Commitee:||Ary, James, Tran, Boi|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 55/06M(E), Masters Abstracts International|
|Subjects:||Computer Engineering, Electrical engineering|
|Keywords:||Embedded system, Face detection, Face tracking, Image processing|
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