Multi-Worker Tracking Algorithm Based on Combined Feature Clustering-Reference-Cited by-同舟云学术

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Multi-Worker Tracking Algorithm Based on Combined Feature Clustering

Published:2022-12-15 Issue: Volume: Page:
ISSN:
Container-title:ICCREM 2022
language:
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Author:

Zhou Ying¹¹²³,Lin Xiao¹¹²³,Luo Zhubang¹¹²³,Guo Hongling¹¹²³

Affiliation:

1. Ph.D. Candidate, Dept. of Construction Management, Tsinghua Univ., Beijing, China.

2. Research Assistant, Dept. of Construction Management, Tsinghua Univ., Beijing, China.

3. Associate Professor, Dept. of Construction Management, Tsinghua Univ., Beijing, China.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484562.030

Reference11 articles.

1. Automated vision tracking of project related entities

2. Cao Z. Simon T. Wei S. E. and Sheikh Y. (2017). “Realtime multi-person 2d pose estimation using part affinity fields.” The IEEE Conference on Computer Vision and Pattern Recognition 7291–7299.

3. A deep learning-based method for detecting non-certified work on construction sites

4. Rule-based approach to recognizing human body poses and gestures in real time.;Hachaj T.;Multimedia Systems,2014

5. Automatic recognition of workers’ motions in highway construction by using motion sensors and long short-term memory (LSTM) networks.;Kim K.;Journal of Construction Engineering and Management,2020

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