Automatic sample key point labeling method, device and system

A key point location and key point technology, applied in the computer field, can solve the problem of insufficient training samples of deep neural network models, and achieve the effect of solving insufficient training samples, good versatility, and high energy efficiency

Pending Publication Date: 2020-05-22
HANGZHOU WEIMING XINKE TECH CO LTD +1
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  • Claims
  • Application Information

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Problems solved by technology

[0004] The present invention proposes an automatic key point labeling technology. The key points are marked on the target template in advance, and the target pictures in different backgrounds in the camera screen are automati

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  • Automatic sample key point labeling method, device and system
  • Automatic sample key point labeling method, device and system
  • Automatic sample key point labeling method, device and system

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[0039] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0040] It should be noted that, unless otherwise specified, technical terms or scientific terms used in this application shall have the usual meanings understood by those skilled in the art to which this application belongs.

[0041] In addition, the terms "first" and "second", etc. are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "include" and "have", as well as any variations the...

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Abstract

The invention provides an automatic sample key point labeling method, device and system, and the method comprises the following steps: receiving a real-time image, and extracting SIFT features of thereal-time image; calculating a matching point according to the SIFT features of a target template image and the SIFT features of the real-time image; calculating a transmission transformation matrix from the target template image to the real-time image according to the matching point; calculating the positions of key point positions in the target template image in the real-time image according tothe transmission transformation matrix; and storing the real-time image and the corresponding key point positions as sample data. According to the method, an existing template matching technology is utilized, targets and corresponding key points under different backgrounds are matched in real time, and high-quality image-key point sample pairs are acquired in batches. Compared with a traditional manual sample labeling method, the method is higher in efficiency and better in universality.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to an automatic sample key point labeling method, device and system. Background technique [0002] The current deep learning technology has greatly improved the level of object detection and classification in the industry. The current mainstream deep learning technology requires a large number of labeled samples for training, and sample labeling requires manual labeling. Especially in the fields of key point detection and semantic segmentation, manual annotation is inefficient and expensive. And in actual production applications, there is a great demand for key point detection of specific objects, but due to the small number of labeled samples, the existing deep network cannot be trained well and cannot achieve the expected goal. [0003] At present, deep neural networks can achieve accuracy comparable to humans under a large amount of training data, but the training o...

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/757G06V10/462
Inventor 林志敏李明昊张高瀚王韬
Owner HANGZHOU WEIMING XINKE TECH CO LTD
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