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Method, device and equipment for detecting shelf stockout rate based on depth image information

A deep image and information detection technology, which is applied in the field of detection of shelf out-of-stock rate based on deep image information, can solve the problems of low accuracy and poor real-time performance of shelf out-of-stock, and achieve the effect of improving real-time performance, efficiency and accuracy

Active Publication Date: 2021-01-12
上海汉时信息科技有限公司
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Problems solved by technology

[0004] The present invention provides a method, device and equipment for detecting shelf out-of-stock rate based on depth image information, which can solve the problems of low accuracy and poor real-time performance of shelf out-of-stock detection. The implementation of the technical solution of the present invention is as follows:

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  • Method, device and equipment for detecting shelf stockout rate based on depth image information
  • Method, device and equipment for detecting shelf stockout rate based on depth image information

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[0060] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

[0061] The terminology used in this application is for the purpose of describing particular embodiments only, and is not intended to limit the application. As used in this application and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the term...

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Abstract

The invention relates to a method, a device and equipment for detecting a shelf stockout rate based on depth image information. The method comprises the following steps: acquiring a shelf depth imageand shelf display information of a target shelf, wherein the shelf display information comprises price tag information and shed grid information of a plurality of commodities; according to the depth value of each pixel point in the shelf depth image, the price tag information and the shed grid information, obtaining the depth value of each pixel point in the price tag boundary frame and the depthvalue of each pixel point in the shed grid boundary frame; calculating a depth mean value of pixel points in the price tag bounding box, and recording the depth mean value as a price tag depth value;obtaining a stockout depth threshold corresponding to the commodity according to the preset stockout sensitivity and the price tag depth value corresponding to the commodity; and detecting the stockout rate of each commodity in the target shelf based on the number of the target pixel points in the shed boundary frame corresponding to the commodity and the total number of the pixel points in the shed boundary frame corresponding to the commodity. Compared with the prior art, the accuracy and efficiency of shelf stockout detection are improved.

Description

technical field [0001] The invention belongs to the technical field of smart supermarkets, and in particular relates to a method, device and equipment for detecting shelf out-of-stock rates based on depth image information. Background technique [0002] With the rapid development of artificial intelligence technology and retail economy, intelligent management technologies for supermarkets and convenience stores are constantly emerging. Digital shelves are an important link in smart retail technology, and the out-of-stock detection technology for digital shelves is an important factor affecting product sales. [0003] In the prior art, the detection of out-of-stock on the shelf mainly relies on manual inventory inspection and gravity sensors to sense the weight of goods. On the one hand, with the expansion of the scale of supermarkets, manual inventory inspection is not only time-consuming and labor-intensive, but also has low accuracy and poor real-time performance; on the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06Q10/08
CPCG06Q10/087G06V20/36G06V10/25
Inventor 李汪佩侯世国张晶朱文杰金小平庄艺唐
Owner 上海汉时信息科技有限公司
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