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Hand joint positioning and local region area calculation method, processor and memory

A positioning method and hand technology, applied in the field of measurement, can solve the problems of detection, inability to accurately locate the local area of ​​hand joints, etc., and achieve the effect of accurate follow-up research

Active Publication Date: 2021-11-30
江苏未来网络集团有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The embodiment of the present application provides a calculation method for hand joint positioning and local area area, so as to at least solve the problem in the prior art that hand joint positioning and local area area detection cannot be performed accurately

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  • Hand joint positioning and local region area calculation method, processor and memory
  • Hand joint positioning and local region area calculation method, processor and memory
  • Hand joint positioning and local region area calculation method, processor and memory

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Embodiment Construction

[0051] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0052] It should be noted that the steps shown in the flowcharts of the accompanying drawings may be performed in a computer system, such as a set of computer-executable instructions, and that although a logical order is shown in the flowcharts, in some cases, The steps shown or described may be performed in an order different than here.

[0053] Since there is no supervised large-scale data set of 45 key points of 15 joints of the hand at home and abroad, the fully automatic target detection algorithm based on the neural network is currently unable to achieve accurate positioning of the hand. Therefore propose a figure 1 The calculation method for the positioning of the hand joints show...

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Abstract

The invention discloses a hand joint positioning and local region area calculation method, which comprises the following steps: obtaining point location data of a hand, the point location data comprises coordinate data and color data, and the point location data is obtained by scanning a hand image with a hand point location identifier, the hand point position marks being located at the two ends of the joint dividing the hand structure into a far joint, a middle joint, a near joint and a palm, and forming four point position types including a far node position, a middle node position, a near node position and a palm point position divided according to the hand structure; rotating the center of each point position around a rotating point to be in a hand vertical state, where the rotating point is the mass center of each hand point position forming a palm; and completing the positioning of the corresponding position of the hand structure according to the point location type and the coordinates of the point location center. According to the invention, the problems of accurate positioning of hand joints and local area detection are solved, so that more accurate follow-up research can be carried out on hands.

Description

technical field [0001] This application relates to the field of measurement, in particular, to a method and device for knuckle positioning and area acquisition. Background technique [0002] In some application scenarios, it is necessary to precisely locate the joints of the hand and obtain the area of ​​the hand area composed of adjacent joints, so as to obtain subsequent data related to the position of the hand joints and the area of ​​the corresponding hand area. [0003] With the advent of neural network algorithms, algorithms for fully automatic object detection in images already exist. However, in the current existing technology, the neural network algorithm for calculating the relevant data of the hand with fully automatic image target detection mainly focuses on gestures. For example, Google MediaPipe Holistic has more than 540 key points (33 postures, 21 hands and 468 Face Keypoints) provide a unified topology and achieve near real-time performance on mobile device...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/62G06T7/70G06T7/90
CPCG06T7/62G06T7/70G06T7/90G06T2207/30196
Inventor 陈虎涂燕晖陈一昕
Owner 江苏未来网络集团有限公司