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This paper addresses the problem of determining a person's body and head orientations while tracking the person in an indoor environment monitored by a single top-view camera. The challenging part of this problem lies in the wide range of human postures depending on the position of the camera and articulations of the pose. In this work, a two-level cascaded particle filter approach is introduced to...
Knowing the visual attention field of a monitored subject is of great value for many applications including surveillance and marketing. This paper proposes first to track peoplepsilas bodies, and then estimates visual attention field for each human using head pose information. The proposed head pose technique aims at estimating the yaw angle only. The method is shown to operate on monocular color...
In this paper, we proposed an enhanced kernel based algorithm for visual tracking based on the video sequences captured from a fixed camera on the top of the scene. The technique presented here employs the image color intensity information and the local binary pattern (LBP) to construct a four dimensional histogram representative of the color intensity values and the texture of the target under study...
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