We propose a new method for human action recognition from video sequences using latent topic models. Video sequences are represented by a novel “bag-of-words” representation, w...
We present an interactive, hybrid human-computer method for object classification. The method applies to classes of objects that are recognizable by people with appropriate expert...
Motion capture data is an effective way of synthesizing human motion for many interactive applications, including games and simulations. A compact, easy-to-decode representation i...
Philippe Beaudoin, Pierre Poulin, Michiel van de P...
We propose to model relative attributes1 that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can captur...
The navigation activity is an every day practice for any human being capable of locomotion. Our objective in this work is to reproduce this crucial human activity inside virtual e...