We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
In this paper, we propose a new gesture recognition model for a set of both one-hand and two-hand gestures based on the dynamic Bayesian network framework which makes it easy to r...
We address the problem of object recognition in computer vision. We represent each model and the scene in the form of Attributed Relational Graph. A multiple region representation...
In this paper we develop an algorithm for action recognition and localization in videos. The algorithm uses a figurecentric visual word representation. Different from previous ap...
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...