Machine Learning-Based Risk Analysis for Construction Worker Safety from Ubiquitous Site Photos and Videos
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[1] Peter E.D. Love,et al. Computer vision applications in construction safety assurance , 2020 .
[2] Mani Golparvar-Fard,et al. Real-Time and Automated Recognition and 2D Tracking of Construction Workers and Equipment from Site Video Streams , 2012 .
[3] Xiaochun Luo,et al. Vision-based detection and visualization of dynamic workspaces , 2019, Automation in Construction.
[4] L McAtamney,et al. RULA: a survey method for the investigation of work-related upper limb disorders. , 1993, Applied ergonomics.
[5] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Nicola Paltrinieri,et al. Learning about risk: Machine learning for risk assessment , 2019, Safety Science.
[7] Patricio A. Vela,et al. Construction performance monitoring via still images, time-lapse photos, and video streams: Now, tomorrow, and the future , 2015, Adv. Eng. Informatics.
[8] Mani Golparvar-Fard,et al. Potential of big visual data and building information modeling for construction performance analytics: An exploratory study , 2017 .
[9] Silvio Savarese,et al. Structural-RNN: Deep Learning on Spatio-Temporal Graphs , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[10] O Karhu,et al. Correcting working postures in industry: A practical method for analysis. , 1977, Applied ergonomics.
[11] Jixiu Wu,et al. Automatic detection of hardhats worn by construction personnel: A deep learning approach and benchmark dataset , 2019, Automation in Construction.
[12] Brenda McCabe,et al. Automated Visual Recognition of Dump Trucks in Construction Videos , 2012, J. Comput. Civ. Eng..
[13] Juan Carlos Niebles,et al. Vision-based action recognition of earthmoving equipment using spatio-temporal features and support vector machine classifiers , 2013, Adv. Eng. Informatics.
[14] Rafael Sacks,et al. Construction Job Safety Analysis , 2010 .
[15] SangHyeok Han,et al. Monocular Vision-Based Framework for Biomechanical Analysis or Ergonomic Posture Assessment in Modular Construction , 2020, J. Comput. Civ. Eng..
[16] Hong Zhang,et al. Personalized method for self-management of trunk postural ergonomic hazards in construction rebar ironwork , 2018, Adv. Eng. Informatics.
[17] John A. Gambatese,et al. Population and Initial Validation of a Formal Model for Construction Safety Risk Management , 2010 .
[18] Amir H. Behzadan,et al. Deep learning for site safety: Real-time detection of personal protective equipment , 2020 .
[19] Peter E.D. Love,et al. A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory , 2018 .
[20] Kaiming He,et al. Mask R-CNN , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[21] Mingyuan Zhang,et al. A critical review of vision-based occupational health and safety monitoring of construction site workers , 2020, Safety Science.
[22] L Punnett,et al. PATH: a work sampling-based approach to ergonomic job analysis for construction and other non-repetitive work. , 1996, Applied ergonomics.
[23] Feniosky Peña-Mora,et al. Vision-Based Detection of Unsafe Actions of a Construction Worker: Case Study of Ladder Climbing , 2013, J. Comput. Civ. Eng..
[24] Mi Zhu,et al. Recognition of High-Risk Scenarios in Building Construction Based on Image Semantics , 2020, J. Comput. Civ. Eng..
[25] Xiaochun Luo,et al. Capturing and Understanding Workers’ Activities in Far‐Field Surveillance Videos with Deep Action Recognition and Bayesian Nonparametric Learning , 2018, Comput. Aided Civ. Infrastructure Eng..
[26] Peter E.D. Love,et al. Falls from heights: A computer vision-based approach for safety harness detection , 2018, Automation in Construction.
[27] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[28] Svein J. Knapskog,et al. Real-Time Risk Assessment with Network Sensors and Intrusion Detection Systems , 2005, CIS.
[29] Heng Li,et al. Estimating Worker-Centric 3D Spatial Crowdedness for Construction Safety Management Using a Single 2D Camera , 2019, J. Comput. Civ. Eng..
[30] Zhongke Shi,et al. Vision-based action recognition of construction workers using dense trajectories , 2016, Adv. Eng. Informatics.
[31] SangHyun Lee,et al. Computer vision techniques for construction safety and health monitoring , 2015, Adv. Eng. Informatics.
[32] Ioannis Brilakis,et al. Construction worker detection in video frames for initializing vision trackers , 2012 .
[33] Mani Golparvar-Fard,et al. Vision-based workface assessment using depth images for activity analysis of interior construction operations , 2014 .
[34] Dario Pavllo,et al. 3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Mani Golparvar-Fard,et al. Human-object interaction recognition for automatic construction site safety inspection , 2020 .
[36] M. Golparvar-Fard,et al. Vision-Based Construction Worker Activity Analysis Informed by Body Posture , 2020, J. Comput. Civ. Eng..
[37] S Hignett,et al. Rapid entire body assessment (REBA). , 2000, Applied ergonomics.
[38] Heng Li,et al. Computer vision aided inspection on falling prevention measures for steeplejacks in an aerial environment , 2018, Automation in Construction.
[39] Xiaochun Luo,et al. Towards efficient and objective work sampling: Recognizing workers' activities in site surveillance videos with two-stream convolutional networks , 2018, Automation in Construction.
[40] Yang Miang Goh,et al. Safety leading indicators for construction sites: A machine learning approach , 2018, Automation in Construction.
[41] Xiaochun Luo,et al. Joint-Level Vision-Based Ergonomic Assessment Tool for Construction Workers , 2019, Journal of Construction Engineering and Management.
[42] Peter E.D. Love,et al. Convolutional neural networks: Computer vision-based workforce activity assessment in construction , 2018, Automation in Construction.
[43] Man-Woo Park,et al. Hardhat-Wearing Detection for Enhancing On-Site Safety of Construction Workers , 2015 .
[44] Mani Golparvar-Fard,et al. A Framework for Model-Driven Acquisition and Analytics of Visual Data Using UAVs for Automated Construction Progress Monitoring , 2015 .
[45] Jochen Teizer,et al. Real-time construction worker posture analysis for ergonomics training , 2012, Adv. Eng. Informatics.
[46] Evangelos A. Yfantis,et al. Hard-Hat Detection for Construction Safety Visualization , 2015 .
[47] Tao Cheng,et al. Real-time resource location data collection and visualization technology for construction safety and activity monitoring applications , 2013 .
[48] Claudio Delrieux,et al. Ergonomic risk assessment based on computer vision and machine learning , 2020, Comput. Ind. Eng..
[49] Rafael Sacks,et al. Spatial and Temporal Exposure to Safety Hazards in Construction , 2009 .
[50] Xiaochun Luo,et al. Detecting non-hardhat-use by a deep learning method from far-field surveillance videos , 2018 .
[51] Hubo Cai,et al. Two-step long short-term memory method for identifying construction activities through positional and attentional cues , 2019, Automation in Construction.
[52] SangUk Han,et al. Tracking-based 3D human skeleton extraction from stereo video camera toward an on-site safety and ergonomic analysis , 2016 .
[53] Heng Li,et al. Ergonomic posture recognition using 3D view-invariant features from single ordinary camera , 2018, Automation in Construction.
[54] Jacob Cohen,et al. The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability , 1973 .
[55] Kaiming He,et al. Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[56] Yuxuan Wang,et al. Onsite video mining for construction hazards identification with visual relationships , 2019, Adv. Eng. Informatics.
[57] Rafiq M Choudhry,et al. Behavior-based safety on construction sites: a case study. , 2014, Accident; analysis and prevention.
[58] Gerardo Cupido,et al. Cognitive Approach to Construction Safety: Task Demand-Capability Model , 2009 .
[59] Yoshua Bengio,et al. Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling , 2014, ArXiv.