0000000000185676
AUTHOR
Khalil Khattab
Embedded System Study for Real Time Boosting Based Face Detection
This paper describes a study for a real time embedded face detection system. Recently, the boosting based face detection algorithms proposed by [(Viola, P and Jone, M, 2001); (Lienhart, R, et al., 2003)] have gained a lot of attention and are considered as the fastest accurate face detection algorithms today. However, the embedded implementation of such algorithms into hardware is still a challenge, since these algorithms are heavily based on memory access. A sequential implementation model is built showing its lack of regularity in time consuming and speed of detection. We propose a parallel implementation that exploits the parallelism and the pipelining in these algorithms. This implement…
Real Time Robust Embedded Face Detection Using High Level Description
Face detection is a fundamental prerequisite step in the process of face recognition. It consists of automatically finding all the faces in an image despite the considerable variations of lighting, background, appearance of people, position/orientation of faces, and their sizes. This type of object detection has the distinction of having a very large intra-class, making it a particularly difficult problem to solve, especially when one wishes to achieve real time processing. A human being has a great ability to analyze images. He can extract the information about it and focus only on areas of interest (the phenomenon of attention). Thereafter he can detect faces in an extremely reliable way.…