In Computer Vision, two-dimensional shape classifcation is a complex and well studied topic, often basic for three-dimensional object recognition. Object contours are a widely cho...
To explore the Perturb and Combine idea for estimating probability densities, we study mixtures of tree structured Markov networks derived by bagging combined with the Chow and Liu...
Sourour Ammar, Philippe Leray, Boris Defourny, Lou...
This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environ...
Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha ...
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...
Markov random fields with higher order potentials have emerged as a powerful model for several problems in computer vision. In order to facilitate their use, we propose a new rep...