Efficient spring system optimization for part-based visual tracking

Part-based trackers typically use visual and geometric constraints to find the most optimal positions of the parts in the constellation. Recently, spring systems was successfully applied to model these constraints. In this paper we propose an optimization method developed for multi-dimensional spring systems, which can be integrated in the part-based tracking model. The experimental analysis shows that our optimization method outperforms theconjugated gradient descend optimization in terms of convergence speed, accuracy and numerical stability.