This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
In this paper, we examine the problem of overcomplete representations and provide new insights into the problem of stable recovery of sparse solutions in noisy environments. We es...
This paper addresses long term tracking of multiple objects with occlusions. Bayesian networks are used to model the interaction among the detected tracks and for conflict managem...
With the recent efforts made by computer vision researchers,
more and more types of features have been designed
to describe various aspects of visual characteristics.
Modeling s...
Liangliang Cao, Jiebo Luo, Feng Liang, Thomas S. H...
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...