Human body identification method and device

Abstract

The invention provides a human body identification method and a human body identification device. The method comprises the steps of acquiring image information; carrying out deep processing on the image information to obtain a depth image and a color image; carrying out human body detection of a deep CNN (Convolutional Neural Network) on the color image and determining a human body boundary frame in the color image; judging whether a unique human body exists in a human body boundary frame area, corresponding to the human body boundary frame, in the depth image; if two or more human bodies exist in the human body boundary frame area, separating the two or more human bodies; and determining the number of the human bodies in the image information according to the number of the human bodies in the human body boundary frame area in the depth image. According to the human body identification method and the human body identification device, secondary identification for the human bodies identified in the color image is realized based on the depth image, the overlapped human bodies are prevented from being misjudged as one human body, the human body identification is assisted by use of the image information of the depth image, and thus the accuracy degree of the human body identification is improved.

Description

technical field [0001] The present application relates to the technical field of robot manufacturing, and in particular to a human body recognition method and device. Background technique [0002] With the rapid development of science and technology, robot manufacturing technology has also developed rapidly, and the application of robots has gradually entered the home service industry. [0003] The property service robot is a robot that is not affected by the environment and temperature and can dynamically realize user identification. This type of robot needs to have excellent identification ability in user identification, so the requirements for human body identification are very high. [0004] At present, traditional property service robots use high-definition cameras to capture user image information, and analyze the captured user image information to achieve the purpose of human body recognition. However, in the actual application process, in the user image information ...

AI Technical Summary

Problems solved by technology

However, in the actual application process, in the user image information captured by the high-definition camera, multiple users often overlap in one area. Serious multiple users are treated as one user by default, which is obviously not in line with reality

Therefore, the accuracy of existing human body recognition methods is low

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