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This paper presents a novel video-based human fall detection system that can detect a human fall in real-time with a high detection rate. This fall detection system is based on an ingenious combination of skeleton feature and human shape variation, which can efficiently distinguish “fall-down” activities from “fall-like” ones. The experimental results indicate that the proposed human fall detection...
This paper proposes a novel human action recognition approach which represents each video sequence by a cumulative skeletonized images (called CSI) in one action cycle. Normalized-polar histogram corresponding to each CSI is computed. That is the number of pixels in CSI which is located in the certain distance and angles of the normalized circle. Using hierarchical classification in two levels, human...
In order to achieve good tracking results in single camera environment, the human pose of recognition, based on a skeleton and texture model of video algorithms to identify the body is proposed. Single-camera in the background and complexity of the environment, the target audience can only show 2-D information. The algorithm will be the first skeleton to the human body in accordance with the balance...
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