This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
Current approaches to automated analysis have focused on a small set of prototypic expressions (e.g., joy or anger). Prototypic expressions occur infrequently in everyday life, ho...
Jeffrey F. Cohn, Adena J. Zlochower, James Jenn-Ji...
It is often thought that learning algorithms that track the best solution, as opposed to converging to it, are important only on nonstationary problems. We present three results s...
Abstract. We propose a new tracking technique that is able to capture non-rigid motion by exploiting a space-time rank constraint. Most tracking methods use a prior model in order ...
This paper addresses the problem of tracking multiple targets using a network of communicating robots and stationary sensors. We introduce a Region-based Approach which controls r...