Video analysis method and device based on artificial intelligence, and medium

Abstract

The invention relates to the technical field of artificial intelligence and data processing. The invention provides a video analysis method and a device based on artificial intelligence and a medium.According to the method, an original video can be split to obtain video segments; the dining condition of each table is judged in a targeted manner; feature extraction on each video segment is carriedout by utilizing the model; automatic feature extraction is realized by combining an artificial intelligence means; analysis of features is carried out, analysis data is obtained, connection with a specified sensor is adopted, calling of target data of each video segment collected by the specified sensor is carried out, and calculation is carried out according to the analysis data and the targetdata to obtain a video analysis result, so that comprehensive and targeted analysis can be performed on a video based on an artificial intelligence means, and the analysis efficiency is higher. The invention also relates to the blockchain technology. A plurality of pre-trained models are stored in the blockchain.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence and data processing, in particular to an artificial intelligence-based video analysis method, device and medium. Background technique [0002] With the improvement of social living standards, more and more people go out to eat, and having a "good" chef can bring more economic benefits and a good social image to the restaurant. [0003] Customer satisfaction with the chef's dishes should be the most direct and fundamental criterion for assessing the chef's level, but in actual scenarios, it is difficult to collect customer feedback on the dishes, and the operation is inconvenient. The current assessment method is mainly to evaluate each chef through the chef's daily attendance and the rigid rules and regulations involved in safety production. satisfaction, so there is a lack of assessment of the chef's core competitiveness. [0004] In addition, at present, the monitoring ...

AI Technical Summary

Problems solved by technology

[0003] Customer satisfaction with the chef's dishes should be the most direct and fundamental criterion for assessing the chef's level, but in actual scenarios, it is difficult to collect customer feedback on the dishes, and the operation is inconvenient

The current assessment method is mainly to evaluate each chef through the chef's daily attendance and the rigid rules and regulations involved in safety production. satisfaction, so there is a lack of assessment of the chef's core competitiveness

[0004] In addition, at present, the monitoring videos of various restaurants are either manually analyzed or only face recognition is performed on the videos. The utilization rate of the videos is not high, and the analysis results corresponding to a single analysis method are not comprehensive enough. The way of conducting holistic analysis also leads to low analysis efficiency and lack of pertinence

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