Segmentation and Tracking of Moving Objects on Dynamic Construction Sites
Author:
Affiliation:
1. Assistant Professor, Dept. of Civil and Environmental Engineering, Kennesaw State Univ., Marietta, GA.
2. Ph.D. Student, Dept. of Civil and Environmental Engineering, Kennesaw State Univ., Marietta, GA.
Publisher
American Society of Civil Engineers
Link
https://ascelibrary.org/doi/pdf/10.1061/9780784485262.007
Reference18 articles.
1. Dataset and benchmark for detecting moving objects in construction sites;An X.;Autom Constr,2021
2. Bewley A. Z. Ge L. Ott F. Ramos and B. Upcroft. 2016. “Simple online and realtime tracking.” 2016 IEEE International Conference on Image Processing (ICIP) 3464–3468. IEEE.
3. A context-augmented deep learning approach for worker trajectory prediction on unstructured and dynamic construction sites
4. Impact of loss functions on semantic segmentation in far‐field monitoring
5. Enclosing contour tracking of highway construction equipment based on orientation-aware bounding box using UAV;Guo Y.;Journal of Infrastructure Preservation and Resilience,2023
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