An Intelligent Vision-Based Method of Worker Identification for Industrial Internet of Things (IoT)
نویسندگان
چکیده
With the rapid development of Internet things (IoT) and computer vision (CV), application combining IoT platform CV technology to monitor worker safety has attracted more attention in field industrial information. Worker identification is a prerequisite for management production, helmet can not only protect worker’s head from accidental injuries but also help identify work types workers through different colors. Therefore, this study proposes an intelligent method based on moving personnel detection color characteristics. First, motion objects that contain nonpersonnel are detected by Gaussian mixture model (GMM) extracted generate region interest (RoI) images. Then, multiple-scale histogram oriented gradient (MHOG) features RoI images extracted, identified support vector machine (SVM). Third, workers’ obtained OpenPose mask, GoogLeNet-based transfer learning network established extract realize identification. This tested our dataset, average accuracy multiple combinations reaches 99.43%, which robust angle, scale, occlusion.
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ژورنال
عنوان ژورنال: Wireless Communications and Mobile Computing
سال: 2022
ISSN: ['1530-8669', '1530-8677']
DOI: https://doi.org/10.1155/2022/8641096