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The following is the Research Report on behavior recognition industry in 2020 From China Institute of electronic technology standardization recommended by recordtrend.com. And this article belongs to the classification: research report.
The behavior recognition technology collects and measures the information of the measured target by means of image, video, thermal, force, acceleration, magnetic and other single sensor or multi sensor fusion. Using various technologies such as data mining, machine learning, pattern recognition and so on, the surface and deep features of human behavior are extracted, and various forms of static or moving states such as target posture, standing, walking, running, jumping and so on are accurately expressed. At present, human behavior recognition mainly includes head movement recognition, gesture recognition, gait recognition, basic posture recognition, abnormal posture recognition and so on.
According to different recognition technologies, human behavior recognition can be divided into three main categories: behavior recognition based on computer vision, behavior recognition based on sensor system and behavior recognition based on multimodal data.
(1) After years of research on behavior recognition based on computer vision, scholars at home and abroad have constructed a variety of frameworks in the field of human body detection, mainly divided into video based methods and image-based methods. The key technologies involved include target detection technology, target tracking technology, sequential behavior classification technology, human key point detection technology, gesture recognition technology, optical flow analysis technology, human segmentation technology, attribute analysis technology and gait recognition technology. With the rapid development of deep learning, these key technologies have made breakthrough progress. Behavior recognition algorithm based on computer vision has been widely used in various industries.
(2) With the popularization of artificial intelligence, human behavior recognition based on sensor system has become an important branch of intelligence. This recognition method mainly uses sensors and sensor networks to capture user behavior. Compared with the method of human behavior recognition using vision, this method has less investment and less equipment complexity, and has better space freedom.
(3) With the rise of various new sensors in recent years, multimodal human behavior recognition has gradually become a new research hotspot in the field of behavior recognition. Generally speaking, the basic multi-modal human behavior recognition process is: multi-modal data acquisition, data preprocessing, feature extraction and selection, human behavior recognition algorithm. It is feasible to combine this method with the frame type of computer vision method. Multimodal fusion analysis can improve the accuracy of behavior recognition and bring better user experience.
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