A novel statistical approch for detection and tracking of objects is presented here, which uses both edge and color information in a particle filter. The approach does not need an...
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
This paper breaks with the common practice of using a joint state space representation and performing the joint data association in multi-object tracking. Instead, we present an i...
We present a particle filtering algorithm for robustly tracking the contours of multiple deformable objects through severe occlusions. Our algorithm combines a multiple blob track...
We study efficient importance sampling techniques for particle filtering (PF) when either (a) the observation likelihood (OL) is frequently multimodal or heavy-tailed, or (b) the s...