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A Semantic Consistency-Based Human Clothing Segmentation Method

A semantic segmentation and consistency technology, applied in the field of computer vision, can solve problems such as inability to extract reasonable features, insufficient data volume to limit the effect of deep learning, and achieve good application value, improve the final effect, and improve the effect of accuracy and efficiency.

Active Publication Date: 2022-02-18
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Deep learning can effectively solve the problem of feature representation, but in the face of the lack of sufficient and accurately labeled data sets in clothing segmentation, the lack of data limits the effect of deep learning, and the deformable characteristics of clothing make ordinary Convolution cannot extract reasonable features

Method used

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  • A Semantic Consistency-Based Human Clothing Segmentation Method
  • A Semantic Consistency-Based Human Clothing Segmentation Method
  • A Semantic Consistency-Based Human Clothing Segmentation Method

Examples

Experimental program
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Effect test

Embodiment

[0077] The implementation method of this embodiment is as described above, and the specific steps will not be described in detail. The following only shows the effect of the case data. The present invention is implemented on three data sets with ground-truth labels, namely:

[0078] Fashionista v0.2 dataset: This dataset contains 685 images with 56 categories of semantic labels.

[0079] Refined Fashionista dataset: This dataset contains 685 images with 25 categories of semantic labels.

[0080] CFPD dataset: This dataset contains 2682 images with 23 categories of semantic labels.

[0081] In this example, a picture is selected for each data set to conduct an experiment. First, the closest picture is obtained by calculating the similarity, and then the features of the two pictures are extracted respectively, and the adjacent pairs of this group of pictures in the flow space are compared. Relationships are jointly modeled to obtain the final semantic segmentation graph, such ...

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Abstract

The invention discloses a human body clothing segmentation method based on semantic consistency, which is used for analyzing the semantic situation of the clothing area of ​​each frame under the condition of a single frame of a single person's clothing picture. Specifically, it includes the following steps: Obtain an image data set for training human clothing segmentation, and define the algorithm goal; find its adjacent pictures in the semantic space for each single frame image in the data set and form a picture pair; for each group of pictures Jointly model the adjacent relationship in the flow space; establish a prediction model for clothing segmentation; use the prediction model to analyze the semantic information of the clothing in the picture. The present invention is suitable for clothing segmentation analysis in real images, and has better effect and robustness in the face of various complex situations.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method for segmenting human clothing based on semantic consistency. Background technique [0002] As a low-level visual technology, clothing semantic segmentation is often used as auxiliary information for some high-level visual tasks, such as clothing retrieval and clothing attribute analysis. The goal of clothing segmentation is to give an image and predict the classification label of each pixel in the image. The key factors for clothing segmentation mainly include the large apparent differences within clothing categories, the non-rigidity of clothing, and the extreme deformability of clothing. Traditional methods generally regard the task of clothing segmentation as a semantic segmentation problem. Although some methods have made breakthroughs in classification accuracy, they do not make full use of the information of existing data. [0003] Due to the effectiveness of stati...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/26G06V10/82G06V40/10G06N3/04
CPCG06V40/10G06V10/267G06N3/045
Inventor 李玺吉炜
Owner ZHEJIANG UNIV
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