Tushar Agrawal

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The articulate motion of the hand makes it very difficult to track the hands while performing a gesture. Simultaneous tracking of both hands needs to deal with large interframe variations in shape, clutter and mutual occlusion. In this paper, we present a robust method for localizing the hand region by tracking even in the presence of severe occlusion. We(More)
Localization is an important topic in the field of mobile robotics. It is the process of estimating the position and orientation of a mobile robot. Several probabilistic techniques are available for this purpose, some of which use a compass sensor to directly determine current orientation. This sensor is highly susceptible to magnetic interference. Here, we(More)
Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from(More)
AstroStat is an easy-to-use tool for performing statistical analysis on data. It has been designed to be compatible with Virtual Observatory (VO) standards thus enabling it to become an integral part of the currently available collection of VO tools. A user can load data in a variety of formats into AstroStat and perform various statistical tests using a(More)
In this paper a scheme is presented for recognizing hand gestures using the output of a hand tracker which tracks a rectangular window bounding the hand region. A hierarchical scheme for dynamic hand gesture recognition is proposed based on state representation of the dominant feature trajectories using an a priori knowledge of the way in which each gesture(More)
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