计算机视觉
人工智能
经济短缺
计算机科学
跳跃式监视
像素
最小边界框
单目视觉
图像(数学)
语言学
哲学
政府(语言学)
作者
Xuzhong Yan,Zhang Hong,Heng Li
摘要
Abstract Struck‐by accidents often cause serious injuries in construction. Monitoring of the struck‐by hazards in terms of spatial relationship between a worker and a heavy vehicle is crucial to prevent such accidents. The computer vision‐based technique has been put forward for monitoring the struck‐by hazards but there exists shortages such as spatial relationship distortion due to two‐dimensional (2D) image pixels‐based estimation and self‐occlusion of heavy vehicles. This study is aimed to address these problems, including the detection of workers and heavy vehicles, three‐dimensional (3D) bounding box reconstruction for the detected objects, depth and range estimation in the monocular 2D vision, and 3D spatial relationship recognition. A series of experiments were conducted to evaluate the proposed method. The proposed method is expected to estimate 3D spatial relationship between construction worker and heavy vehicle in a real‐time and view‐invariant manner, thus enhancing struck‐by hazards monitoring at the construction site.
科研通智能强力驱动
Strongly Powered by AbleSci AI