Zhen-Peng Bian

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The elderly population is increasing rapidly all over the world. One major risk for elderly people is fall accidents, especially for those living alone. In this paper, we propose a robust fall detection approach by analyzing the tracked key joints of the human body using a single depth camera. Compared to the rivals that rely on the RGB inputs, the proposed(More)
This paper presents an improved skeleton extraction from depth video for fall detection based on fast randomized decision forest (RDF) algorithm. Due to the human's body orientation changes dramatically during falling, it reduces the accuracy of tracking. The human's orientation needs to be corrected before the process by RDF. A rotation to correct the(More)
This paper proposes a human computer interface using a single depth camera for quadriplegic people. The nose position is employed to control the cursor along with the commands provided by mouth's status. The detection of nose position and mouth's status is based on randomized decision tree algorithm.The experimental results show that the proposed interface(More)
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