TY - GEN
T1 - Computer Vision Technologies and Machine Learning Algorithms for Construction Safety Management
T2 - International Conference on Construction and Real Estate Management 2019: Innovative Construction Project Management and Construction Industrialization, ICCREM 2019
AU - Liu, Yongyue
AU - Wang, Yaowu
AU - Li, Xiaodong
N1 - Publisher Copyright:
© 2019 American Society of Civil Engineers.
PY - 2019
Y1 - 2019
N2 - Computer vision technologies (CV) have been widely used for object detecting, tracking, and recognizing in the construction industry with machine learning algorithms (ML). This paper aim to make a comprehensive and systematic review of 438 CV related papers in construction safety management (CSM), and 169 camera related computer vision technologies (CRCV) papers were extracted. Finally, 29 camera related computer vision technologies and machine learning algorithms (CRCV-ML) papers were recognized for analyzing. Data collection, chronological, project types, CRCV, and learning algorithms distributions are proposed objectively by three-stage searching process. In discussion section, main research findings together with trends and gaps were gained. These results may help researchers identify the gaps and trends of CV and ML, and can serve as a guidance for future application research.
AB - Computer vision technologies (CV) have been widely used for object detecting, tracking, and recognizing in the construction industry with machine learning algorithms (ML). This paper aim to make a comprehensive and systematic review of 438 CV related papers in construction safety management (CSM), and 169 camera related computer vision technologies (CRCV) papers were extracted. Finally, 29 camera related computer vision technologies and machine learning algorithms (CRCV-ML) papers were recognized for analyzing. Data collection, chronological, project types, CRCV, and learning algorithms distributions are proposed objectively by three-stage searching process. In discussion section, main research findings together with trends and gaps were gained. These results may help researchers identify the gaps and trends of CV and ML, and can serve as a guidance for future application research.
UR - https://www.scopus.com/pages/publications/85072940369
U2 - 10.1061/9780784482308.008
DO - 10.1061/9780784482308.008
M3 - 会议稿件
AN - SCOPUS:85072940369
T3 - ICCREM 2019: Innovative Construction Project Management and Construction Industrialization - Proceedings of the International Conference on Construction and Real Estate Management 2019
SP - 67
EP - 81
BT - ICCREM 2019
A2 - Wang, Yaowu
A2 - Al-Hussein, Mohamed
A2 - Shen, Geoffrey Q. P.
PB - American Society of Civil Engineers (ASCE)
Y2 - 21 May 2019 through 24 May 2019
ER -