Parallel Appearance-Adaptive Models for Real-Time Object Tracking Using Particle Swarm Optimization

Boguslaw Rymut and Bogdan Kwolek: Parallel Appearance-Adaptive Models for Real-Time Object Tracking Using Particle Swarm Optimization; Int. Conf. on Computational Collective Intelligence – Technologies and Applications, 2011, Computational Collective Intelligence. Technologies and Applications, Lecture Notes in Computer Science, Vol. 6923, Springer Berlin Heidelberg, 2011, pp. 455-464.

Abstract

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. We show the performance of the algorithm that was evaluated on multi-core CPUs. Experimental results demonstrate the performance of the algorithm in comparison to our GPU based implementation of the object tracker using appearance-adaptive models. The algorithm has been tested on real image sequences.