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- W2020144372 abstract "We propose a novel system for extracting multiple people in crowded scenes by employing LED 3D range sensor. This new kind of device can capture depth image at a relatively high frame speed, which makes the extraction of dynamic objects possible. However, it suffers from the strong noise caused by the environment illumination. Here we propose a novel method for multiple people extraction by integrating an improved version of mean-shift clustering algorithm and total variation based denoising technique. When handling the depth image, it is considered both as a point cloud as well as a 2D image. In this way, different properties of the depth image are sufficiently exploited. The proposed method can fully automatically extract multiple people in a cluttered environment, even from a mobile platform. The experiment conducted at the platform of a railway station demonstrates the effectiveness of our proposed algorithm." @default.
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- W2020144372 date "2010-10-01" @default.
- W2020144372 modified "2023-09-23" @default.
- W2020144372 title "Multiple people extraction using 3D range sensor" @default.
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- W2020144372 doi "https://doi.org/10.1109/icsmc.2010.5642334" @default.
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