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A commodity alignment method based on unsupervised feature point detection

A feature point detection, unsupervised technology, applied in the field of artificial intelligence, can solve the problems of product alignment, impact on recognition accuracy, high cost, etc., to achieve the effect of easy identification, saving labeling costs, and high accuracy

Active Publication Date: 2019-01-11
SUN YAT SEN UNIV
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

2. Most of the product recognition tasks do not align the products
[0004] The shortcomings of the existing technology are: 1. Training requires a large amount of labeled image data, and manual labeling or design of object structures is very costly for most object categories
2. Due to the high cost of labeling and the complex product structure, the current product recognition task is not aligned, which has a certain impact on the recognition accuracy

Method used

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  • A commodity alignment method based on unsupervised feature point detection
  • A commodity alignment method based on unsupervised feature point detection
  • A commodity alignment method based on unsupervised feature point detection

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Embodiment Construction

[0021] The accompanying drawings are for illustrative purposes only, and should not be construed as limitations on this patent; in order to better illustrate this embodiment, certain components in the accompanying drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art It is understandable that some well-known structures and descriptions thereof may be omitted in the drawings. The positional relationship described in the drawings is for illustrative purposes only, and should not be construed as a limitation on this patent.

[0022] like figure 1 As shown, a product alignment method based on unsupervised feature point detection, which includes the following steps:

[0023] S1. Feature point detection training data preparation;

[0024] S2. Detection frame model training;

[0025] S3. Feature point detection;

[0026] S4. Affine transformation alignment is performed according to the feature point coordi...

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Abstract

The present invention relates to the technical field of artificial intelligence and more particularly to a commodity alignment method based on unsupervised feature point detection. The commodity alignment method based on unsupervised feature point detection comprises the following steps: S1, preparing feature point detection training data; S2, training the detection frame model; 3, feature point detection; 4, carry out affine transformation alignment according to that coordinate of the characteristic points. The invention can be used on the commodity subsequent identification network after thefeature points are detected and aligned, and the identification accuracy rate is obviously higher than that of the commodity subsequent identification network without alignment, because the network is easier to identify the forward object than the inclined object. For the existing supervised feature point alignment, this method can save labeling cost.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, and more specifically, to a product alignment method based on unsupervised feature point detection. Background technique [0002] At present, there is no uniform alignment method for no product, and most of the related tasks are not aligned. The existing alignment methods are also supervised and marked with feature points first, but manually marked feature points are not rude for different products. Great, and the cost of manual annotation is very high. Therefore, it is very meaningful to use it in the commodity field if it can unsupervised and adaptively find commodity structure feature points that can resist rotation. [0003] The prior art is: 1. The existing commodity feature point detection is to use the labeled data to pre-train the feature point detection model, and then predict and align the feature points of the commodity pictures. 2. Most of the product recogni...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06F16/953
CPCG06Q30/0631G06Q30/0643
Inventor 康乐潘嵘
Owner SUN YAT SEN UNIV
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