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Mean shift object tracking for a SIMD computer

We use SIMD (single instruction multiple data) instructions to implement a popular video object-tracking algorithm in an attempt to achieve the best possible performance on the available hardware. We start with an implementation of the well-known mean shift algorithm with adaptive scale and background-weighted histogram enhancements. Due to its histogramic nature, mean shift is not normally considered worth optimizing with vector instructions. However, when we looked for basic opportunities to exploit SIMD style processing, we in fact discovered several opportunities to exploit SIMD instructions. We compare the tracking efficiency of our implementation with a standard implementation in order to demonstrate the efficiency of the modified technique. In this paper, we present the optimizations we have applied as well as the performance results obtained.