We consider the problem of recognizing human actions from still images. We propose a novel approach that treats the pose of the person in the image as latent variables that will h...
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
This work describes a multi-agent architecture and strategy for trade in simultaneous and related auctions. The proposed SIMPLE Agency combines an integer programming model, machi...
—In this paper, we propose a Multi-Manifold Discriminant Analysis (MMDA) method for face feature extraction and face recognition, which is based on graph embedded learning and un...
A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of ...