In this paper we address two closely related problems. The first is the object detection problem, i.e., the automatic decision of whether a given image represents a known object o...
This paper proposes an approach for retrieving videos based on object trajectories and subtrajectories. First, trajectories are segmented into subtrajectories according to the char...
We investigate a biologically motivated approach to fast visual classification, directly inspired by the recent work [13]. Specifically, trading-off biological accuracy for comput...
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter...
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...