Design of complex image processing systems in ESL
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
AdaBoost face detection on the gpu using Haar-like features
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
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Adaboost algorithm is difficult to implement on embedded platform for real-time face detection by software due to its high computation load and data throughput. This article presents a cell array architecture using parallel technology. Detection procedure can be greatly speeded up with its multipipeline. Besides it makes use of the continuity of image data to decrease the accesses to RAM. This article uses Electronic System Level (ESL) tools to develop and simulate a cycle-accurate model of the cell array architecture. The result shows that cell array architecture with 200MHz clock can process 12 million HAAR features per second and detect faces on a 176*144 image at the frame rate of 103 frames per second, which is 14 times speedup compared with software implementation.