Literature DB >> 32075274

Employing Shadows for Multi-Person Tracking Based on a Single RGB-D Camera.

Wei Gai1, Meng Qi2, Mingcong Ma1, Lu Wang1, Chenglei Yang1,3, Juan Liu1, Yulong Bian1, Gerard de Melo4, Shijun Liu1, Xiangxu Meng1,3.   

Abstract

Although there are many algorithms to track people that are walking, existing methods mostly fail to cope with occluded bodies in the setting of multi-person tracking with one camera. In this paper, we propose a method to use people's shadows as a clue to track them instead of treating shadows as mere noise. We introduce a novel method to track multiple people by fusing shadow data from the RGB image with skeleton data, both of which are captured by a single RGB Depth (RGB-D) camera. Skeletal tracking provides the positions of people that can be captured directly, while their shadows are used to track them when they are no longer visible. Our experiments confirm that this method can efficiently handle full occlusions. It thus has substantial value in resolving the occlusion problem in multi-person tracking, even with other kinds of cameras.

Entities:  

Keywords:  RGB-D camera; multi-person tracking; occlusion; shadow

Year:  2020        PMID: 32075274     DOI: 10.3390/s20041056

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  Multi-Object Tracking Algorithm for RGB-D Images Based on Asymmetric Dual Siamese Networks.

Authors:  Wen-Li Zhang; Kun Yang; Yi-Tao Xin; Ting-Song Zhao
Journal:  Sensors (Basel)       Date:  2020-11-25       Impact factor: 3.576

2.  A Pruning Method for Deep Convolutional Network Based on Heat Map Generation Metrics.

Authors:  Wenli Zhang; Ning Wang; Kaizhen Chen; Yuxin Liu; Tingsong Zhao
Journal:  Sensors (Basel)       Date:  2022-03-04       Impact factor: 3.576

  2 in total

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