Abstract
There is a rapidly growing demand for using intelligent cameras for various applications in surveillance and identification. Most of these applications have real-time demands and require huge processing capacity. Face recognition is one of those applications highly in demand. In this paper we show that we can run face recognition in real-time by implementing the algorithm on an architecture which combines a massively parallel processor with a high performance Digital Signal Processor. In this paper we focus on the INCA+ intelligent camera. It contains a CMOS sensor, a Single Instruction Multiple Data (SIMD) processor [1] and a Very Long Instruction Word (VLIW) processor. The SIMD processor enables high-performance pixel processing and detects the interesting (face) regions from the video. It sends the regions of interest to the VLIW processor, which performs the actual face recognition using a neural network. With this architecture we perform face recognition from a 5-persons database at more than 200 faces per second. The performance is better than most recent high-end professional systems [2].
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