Occlusion and lack of visibility in dense crowded scenes make it very difficult to track individual people correctly and consistently. This problem is particularly hard to tackle i...
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 present a tunable representation for tracking that simultaneously encodes appearance and geometry in a manner that enables the use of mean-shift iterations for tracking. The cl...
This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous globa...
Background: The evaluation of information retrieval techniques has traditionally relied on human judges to determine which documents are relevant to a query and which are not. Thi...