Journal ArticleDOI
A vision-based motion capture and recognition framework for behavior-based safety management
SangUk Han,SangHyun Lee +1 more
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TLDR
A framework of vision-based unsafe action detection for behavior monitoring to provide a robust and automated means for worker observation and indicates that the proposed framework can potentially perform well at detecting predefined unsafe actions in videos.About:
This article is published in Automation in Construction.The article was published on 2013-11-01. It has received 271 citations till now.read more
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Journal ArticleDOI
Computer vision techniques for construction safety and health monitoring
TL;DR: This paper categorizes previous studies into three groups-object detection, object tracking, and action recognition-based on types of information required to evaluate unsafe conditions and acts, and provides researchers insights into advancing knowledge and techniques for computer vision-based safety and health monitoring.
Journal ArticleDOI
A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory
TL;DR: The results reveal that the developed hybrid model (CNN + LSTM) is able to accurately detect safe/unsafe actions conducted by workers on-site and exceeds the current state-of-the-art descriptor-based methods for detecting points of interest on images.
Journal ArticleDOI
Detecting non-hardhat-use by a deep learning method from far-field surveillance videos
TL;DR: In this paper, the authors proposed the use of a high precision, high recall and widely applicable Faster R-CNN method to detect construction workers' non-hardhat-use (NHU) detection.
Journal ArticleDOI
Falls from heights: A computer vision-based approach for safety harness detection
TL;DR: An automated computer vision-based method that uses two convolutional neural network models to determine if workers are wearing their harness when performing tasks while working at heights can be used by construction and safety managers to proactively identify unsafe behavior and take immediate action to mitigate the likelihood of a FFH occurring.
Journal ArticleDOI
Construction performance monitoring via still images, time-lapse photos, and video streams
TL;DR: This paper extensively reviews these state-of-the-art vision-based construction performance monitoring methods and divides them into two categories (namely project level: visual monitoring of civil infrastructure or building elements vs. operation level:Visual monitoring of construction equipment and workers).
References
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Proceedings ArticleDOI
Histograms of oriented gradients for human detection
Navneet Dalal,Bill Triggs +1 more
TL;DR: It is shown experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection, and the influence of each stage of the computation on performance is studied.
Book
Multiple view geometry in computer vision
Richard Hartley,Andrew Zisserman +1 more
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Journal ArticleDOI
Nonlinear component analysis as a kernel eigenvalue problem
TL;DR: A new method for performing a nonlinear form of principal component analysis by the use of integral operator kernel functions is proposed and experimental results on polynomial feature extraction for pattern recognition are presented.
Book
Computer Vision: Algorithms and Applications
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
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