We present a Kalman tracking algorithm that can track a number of very small, low contrast objects through an image sequence taken from a static camera. The issues that we have ad...
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
— Vision is one of the most powerful sensory modalities in robotics, allowing operation in dynamic environments. One of our long-term research interests is mobile manipulation, w...
We present a framework for annotating dynamic scenes involving occlusion and other uncertainties. Our system comprises an object tracker, an object classifier and an algorithm for...
Brandon Bennett, Derek R. Magee, Anthony G. Cohn, ...