Key point detection method and device, electronic equipment and storage medium

A detection method and key point technology, applied in the field of computer vision, can solve the problems of low detection accuracy of key points, inability to fully mine and utilize multi-scale features, etc.

Active Publication Date: 2019-04-12
BEIJING SENSETIME TECH DEV CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, we found that using this method, it is not possible to fully mine and

Method used

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  • Key point detection method and device, electronic equipment and storage medium
  • Key point detection method and device, electronic equipment and storage medium
  • Key point detection method and device, electronic equipment and storage medium

Examples

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Embodiment Construction

[0056] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0057] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.

[0058] The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the term "at least one" herein mean...

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Abstract

The invention relates to a key point detection method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining first feature maps of multiple scales for aninput image, and enabling the scales of the first feature maps to be in a multiple relation; Using a first pyramid neural network to carry out forward processing on each first feature map to obtain second feature maps in one-to-one correspondence with the first feature maps, the second feature maps being the same as the first feature maps in one-to-one correspondence with the second feature maps in scale; carrying out reverse processing on each second feature map by utilizing a second pyramid neural network to obtain third feature maps in one-to-one correspondence with the second feature maps,the scales of the third feature maps being the same as the scales of the second feature maps in one-to-one correspondence with the third feature maps; and performing feature fusion processing on eachthird feature map, and obtaining the position of each key point in the input image by using the feature map after feature fusion processing. The positions of the key points can be accurately extracted.

Description

technical field [0001] The present disclosure relates to the technical field of computer vision, and in particular to a key point detection method and device, electronic equipment and a storage medium. Background technique [0002] Human body key point detection is to detect the position information of key points such as joints or facial features from the human body image, so as to describe the posture of the human body through the position information of these key points. [0003] Because the human body is different in size in the image, the existing technology can usually use the neural network to obtain the multi-scale features of the image, which is used to finally predict the position of the key points of the human body. However, we found that using this method, multi-scale features cannot be fully mined and utilized, and the detection accuracy of key points is low. Contents of the invention [0004] Embodiments of the present disclosure provide a key point detection...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08G06V10/764
CPCG06N3/08G06N3/045G06F18/253G06V40/10G06V2201/033G06V10/82G06V10/764G06V10/806G06F18/2413Y02T10/40G06V10/462G06F18/21
Inventor 杨昆霖田茂清伊帅
Owner BEIJING SENSETIME TECH DEV CO LTD
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