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RRT* is a recent and improved variant of the RRT path finding algorithm. While RRT concentrates on simply finding an initial obstacle-free path, RRT* guarantees eventual convergence to an optimum, collision-free path for any given geometrical environment. On the other hand, the main limitations of RRT* include its slow processing rate and high memory utilization due to the large number of iterations...
In video-conference, the camera is placed at the top of the screen and the user looks at the other user's image on the screen. This misalignment of eye gaze direction degrades the user's experience. To solve this problem, this paper presents an eye gaze correction method using vertical stereo camera. The proposed method matches the eye regions in two images captured by stereo camera and generates...
The Rapidly Exploring Random Tree Star (RRT∗) is an extension of the Rapidly Exploring Random Tree path finding algorithm. RRT∗ guarantees an optimal, collision free path solution but is limited by slow convergence rates and inefficient memory utilization. This paper presents APGD-RRT∗, a variant of RRT∗ which utilizes Artificial Potential Fields to improve RRT∗ performance, providing relatively better...
Detection and Tracking of human being is a very important problem in Computer Vision. Human robot interaction is a very essential need for service robots where robots are required to detect and track human beings in order to provide the required service. In this paper we present an improved novel approach for tracking a target person in crowded environment. We used multi-sensor data fusion approach...
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