Remnant detection method and device, electronic equipment and storage medium
A detection method and technology for residues, which are applied in the fields of detection methods, devices, electronic equipment and storage media for residues, can solve the problems of wrong judgment, missed detection, and low accuracy of residues, so as to improve accuracy and reduce The probability of false detection, the effect of avoiding the influence of lighting changes
Pending Publication Date: 2022-01-18
YANGZHONG INTELLIGENT ELECTRICAL INST NORTH CHINA ELECTRIC POWER UNIV
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[0005] However, the remnant detection method based on background modeling is very sensitive to changes in light, and is easily affected by changes in light, resulting in wrong judgments on remnants. For example, when there is sudden strong light in the monitoring scene, the model is easy to think is a carryover, thus erroneously issuing a carryover alert
The leftover detection method based on deep learning is not greatly affected by light, but it needs to be trained in advance on the object to be detected. Untrained object types cannot be detected, and only trained specific types of leftovers can be detected, which is prone to omissions. detection situation, resulting in low accuracy of carryover detection
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[0063] In order to make the purpose, technical solutions and advantages of the application clearer, the technical solutions in the embodiments of the application will be clearly and completely described below in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are only It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application. In the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined arbitrarily with each other. Also, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.
[0064] The terms "first" and "second" in the specificatio...
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The embodiment of the invention provides a remnant detection method and device, electronic equipment and a storage medium, which are used for improving the accuracy of remnant detection and reducing the false detection probability. The method comprises the following steps: carrying out target detection on a plurality of frames of collected images; acquiring a first image and a second image according to a detection result, wherein the first image is a first frame image, in which a target object is detected, in the multiple frames of images, the second image is a first frame image, in which the target object is not detected, in the multiple frames of images, and the shooting time of the first image is earlier than the shooting time of the second image; performing subtraction on the image pixel matrix of the first image and the image pixel matrix of the second image to obtain a first difference image; and determining a region of which the pixel value is greater than a first preset threshold value in the first difference image as a remnant region.
Description
technical field [0001] The invention relates to the technical field of video monitoring, in particular to a method, device, electronic equipment and storage medium for detecting remnants. Background technique [0002] Detecting leftovers in the surveillance scene is a key task to ensure public safety. For example, debris accumulated at fire exits or safety exits will affect the evacuation of people in emergency situations. At present, there are mainly two common remnant detection methods, one is remnant detection based on background modeling, and the other is specific remnant detection based on deep learning. [0003] Remnant detection based on background modeling mainly includes three steps: background modeling, stationary object detection and object classification. Among them, in the background modeling stage, the algorithm processes the surveillance video stream through methods such as Gaussian mixture model and visual background extraction to obtain the background image...
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IPC IPC(8): G06V20/52
Inventor 刘伟平刘鹏肖传欣胡瑞通
Owner YANGZHONG INTELLIGENT ELECTRICAL INST NORTH CHINA ELECTRIC POWER UNIV