Silhouette-Based On-Site Human Action Recognition in Single-View Video

Liu, Meiyin; Hong, David; Han, SangUk; Lee, Sang Hyun

doi:10.1061/9780784479827.096

Cited by 9 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, there are still problems with automatic detection systems for the absence of hard hats using one or more cameras. For example, S. Du offers a method for detecting the absence of hard hats, based on facial features, information about movement and color [15]. Color-based face recognition methods have two important assumptions: all workers turn to face the camera while working, and all hard hats have the same color.…”

Section: Existing Ppe Control Methodsmentioning

confidence: 99%

Application of vision systems to improve the effectiveness of monitoring compliance with technical safety requirements at industrial facilities

EKimenko

Itmo²,

Ekimenko³

et al. 2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

View full text Add to dashboard Cite

According to the Federal State Statistics Service for 2017, over 25,000 injuries at work were registered in Russia, of which 1,138 were fatal. Studies have shown that most of the injuries in the workplace due to non-compliance with technical safety rules, namely the lack of personal protective equipment or their improper use. To improve the efficiency of monitoring compliance with the rules of technical safety at industrial facilities, this paper discusses the use of vision systems for automatic control of the availability of personal protective equipment at workers in the area of industrial work.

show abstract

Section: Existing Ppe Control Methodsmentioning

confidence: 99%

Application of vision systems to improve the effectiveness of monitoring compliance with technical safety requirements at industrial facilities

EKimenko

Itmo²,

Ekimenko³

et al. 2019

Proceedings of the v International Conference Information Technology and Nanotechnology 2019

View full text Add to dashboard Cite

show abstract

“…Although this method is not restricted by certain conditions (e.g., light source), the image quality obtained is rough (Figure 10). Combined with the follow-up research of Seo et al [38] and Liu et al [52], this behavior detection method can be divided into four steps, including tracking the main body of workers, using the algorithm model to check the background perform segmentation, using histograms to extract features and using classifiers to classify data. While CV-based deep learning has not been widely used, researchers used depth images and stereo cameras to obtain dynamic image information of workers so as to obtain higher-resolution images.…”

Section: Posture Recognition During Constructionmentioning

confidence: 99%

Applications of Computer Vision in Monitoring the Unsafe Behavior of Construction Workers: Current Status and Challenges

Liu

Meng

et al. 2021

Buildings

View full text Add to dashboard Cite

The unsafe behavior of construction workers is one of the main causes of safety accidents at construction sites. To reduce the incidence of construction accidents and improve the safety performance of construction projects, there is a need to identify risky factors by monitoring the behavior of construction workers. Computer vision (CV) technology, which is a powerful and automated tool used for extracting images and video information from construction sites, has been recognized and adopted as an effective construction site monitoring technology for the identification of risky factors resulting from the unsafe behavior of construction workers. In this article, we introduce the research background of this field and conduct a systematic statistical analysis of the relevant literature in this field through the bibliometric analysis method. Thereafter, we adopt a content-based analysis method to depict the historical explorations in the field. On this basis, the limitations and challenges in this field are identified, and future research directions are proposed. It is found that CV technology can effectively monitor the unsafe behaviors of construction workers. The research findings can enhance people’s understanding of construction safety management.

show abstract

Research Trends of Information Technology Application in Construction Workers’ Behavior Monitoring

Yang

et al. 2021

Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate

View full text Add to dashboard Cite

Silhouette-Based On-Site Human Action Recognition in Single-View Video

Cited by 9 publications

References 9 publications

Application of vision systems to improve the effectiveness of monitoring compliance with technical safety requirements at industrial facilities

Application of vision systems to improve the effectiveness of monitoring compliance with technical safety requirements at industrial facilities

Applications of Computer Vision in Monitoring the Unsafe Behavior of Construction Workers: Current Status and Challenges

Research Trends of Information Technology Application in Construction Workers’ Behavior Monitoring

Contact Info

Product

Resources

About