Personnel detection counting method based on deep learning

Abstract

The invention discloses a personnel detection counting method based on deep learning, and the method comprises the steps: 1, carrying out periodic collection of a video monitoring image, and detectingpersonnel based on a FiarMot algorithm; 2, extracting a region of interest of detection personnel and calculating an intersection ratio of the region of interest to a monitoring region; and 3, constructing an adaptive scale LSTM neural network, fusing a full connection layer and wavelet transform features, performing classification by using an SCN classifier, and evaluating and automatically adjusting a network scale according to an entropy loss value of a detection result. The network scale can be automatically adjusted according to the entropy loss value evaluation of the detection result,so that the self-optimization adjustment and reconstruction of the video personnel detection model can be realized, the video personnel detection rate of a specified area in different environments isimproved, and the actual requirements of accuracy and rapidness are met.

Description

technical field [0001] The invention belongs to the field of computer vision, image recognition technology, and deep learning technology, and specifically relates to a method for detecting and counting people based on deep learning. Background technique [0002] Personnel detection and counting has guiding significance for management in some specific occasions. For example, in shopping malls, the estimation of consumers' personnel can be analyzed, and corresponding consumption strategies can be formulated. Personnel detection and counting of scenic spots can regulate the number of tourists and avoid crowded and dangerous areas. , improving safety and visitor satisfaction. [0003] However, the environmental information is diverse, and the current personnel detection and counting model cannot adapt to various complex scenarios, such as the coal mine scene. Get out of the cage. The wellhead environment is complex, and video cannot accurately detect personnel. Contents of t...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the shortcomings of the above-mentioned prior art, the present invention proposes a method of personnel detection and counting based on deep learning, in order to solve the problem of high misrecognition rate of personnel detection and counting in complex scenes, and can be based on the entropy loss of detection results Value evaluation automatically adjusts the network scale, realizes automatic adjustment of the detection model and counts personnel detection, thereby improving the detection rate and counting accuracy of personnel in complex backgrounds, and meeting the actual needs of accuracy and speed

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