This paper introduces “Flocks of Features,” a fast tracking method for non-rigid and highly articulated objects such as hands. It combines KLT features and a learned foregroun...
In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking9 error norms are derived. By using the Ma...
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
In this paper, we introduce a novel incremental subspace based object tracking algorithm. The two major contributions of our work are the Robust PCA based occlusion handling scheme...
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...