Open AccessForeground detection of human targets with abnormal behavior of mechanical operators
Author(s) -
Hui Luo,
Zhixin Liu,
Xia Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1827/1/012087
Subject(s) - computer science , computer vision , artificial intelligence , adaptability , background subtraction , frame (networking) , edge detection , noise (video) , interference (communication) , motion detection , optical flow , subtraction , enhanced data rates for gsm evolution , image processing , pattern recognition (psychology) , motion (physics) , image (mathematics) , pixel , mathematics , channel (broadcasting) , ecology , telecommunications , computer network , arithmetic , biology
Complexity of mechanical production environment has brought a certain degree of interference to human target recognition, so it is necessary to preprocess the target video sequence before target detection. The advantages and disadvantages of various detection methods are compared. Research results show that the inter frame difference method has strong adaptability and the target contour is discontinuous. The optical flow method is suitable for the case of lens motion, which is complex in calculation and poor in noise resistance. ViBe algorithm has good effect in obtaining the target contour, clear edge and less holes, and the operation efficiency is not high. The background subtraction method basically retains the features needed by the moving foreground target behavior recognition and detection, and the processing speed is very fast, which can meet the requirements of real-time processing.