Parallel Appearance-Adaptive Models for Real-Time Object Tracking Using Particle Swarm Optimization
نویسندگان
چکیده
1 This paper demonstrates how appearance adaptive models can be employed for real-time object tracking using particle swarm optimization. The parallelization of the code is done using OpenMP directives and SSE instructions. The performance of our parallel algorithm was evaluated using multi-core CPUs. Experimental results show the performance of the algorithm in comparison to our GPU based implementation of the object tracker. The algorithm has been tested on real image sequences.
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تاریخ انتشار 2011