Interactive behavior recognition method and device, computer equipment and storage medium

Abstract

The invention relates to an interactive behavior recognition method and device, computer equipment and a storage medium. The method comprises the steps of obtaining a to-be-detected image; inputting the to-be-detected image into a preset multi-task model to obtain key points and a detection box of pedestrians in the to-be-detected image, the key points being located in the detection box, and the multi-task model being used for pedestrian detection and human body key point detection; According to the key points of the pedestrian and a preset article shelf image corresponding to the to-be-detected image, determining interaction behavior information of the pedestrian and the corresponding article shelf. By adopting the method, the interaction behavior of the pedestrian and the article can beefficiently identified.

Description

technical field [0001] The present application relates to the technical field of computer vision, in particular to an interactive behavior recognition method, device, computer equipment and storage medium. Background technique [0002] With the advent of the Internet era, the retail industry has entered a stage of rapid development. The future of retail is smart retail, that is, using technologies such as the Internet and big data to perceive users' consumption habits, so as to provide consumers with diversified and personalized services. Products and services, and human-goods interaction behavior recognition is a problem that needs to be solved in the field of smart retail. [0003] The traditional human-goods interaction behavior recognition method generally uses sensor devices such as sound, light, and electricity to realize behavior recognition, which requires high hardware costs, and the usage scenarios are limited, so it cannot be applied to complex environments such a...

AI Technical Summary

Problems solved by technology

[0003] The traditional human-goods interaction behavior recognition method generally uses sensor devices such as sound, light, and electricity to realize behavior recognition, which requires high hardware costs, and the usage scenarios are limited, so it cannot be applied to complex environments such as supermarkets on a large scale; The equipment generates a large amount of video data every day. Analyzing the surveillance video can obtain a lot of information about the interaction between people and goods, but this requires a huge amount of manpower, and there are still problems of low efficiency.

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