This work presents a discriminative training method for
particle filters in the context of multi-object tracking. We
are motivated by the difficulty of hand-tuning the many
mode...
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
In this work we propose an approach to combine audio and video modalities for person tracking using graphical models. We demonstrate a principled and intuitive framework for combi...
Akash Kushal, Mandar Rahurkar, Fei-Fei Li 0002, Je...
Recent studies on visual tracking have shown significant improvement in accuracy by handling the appearance variations of the target object. Whereas most studies present schemes ...
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...