Real-Time Face Recognition on a Mixed SIMD VLIW Architecture
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 project we focus on the INCA+ intelligent camera. It contains a CMOS sensor, a Single Instruction Mul-
tiple 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 high-end professional systems that are in use now [2].
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