research-article

Clothing Identification based on Fused Key Points

Authors:

Zhengguang Xie,

Shaohua HaoAuthors Info & Claims

ICIAI '19: Proceedings of the 2019 3rd International Conference on Innovation in Artificial Intelligence

Pages 116 - 120

https://doi.org/10.1145/3319921.3319949

Published: 15 March 2019 Publication History

Abstract

In order to solve the problem of low accuracy of multi-category clothing recognition, an algorithm combining global and local features of clothing is proposed, which is aimed at solving the decrease of clothing recognition rate caused by changes of perspective and attitude and complexity of images.Based on the deep convolutional neural network, the algorithm locates the key points of clothing, excavates the key points image blocks, fuses the low-level visual information of the key points image blocks and the high-level semantic information of the whole image for clothing classification.This paper conducts experiments on the Deepfashion dataset, uses keras for data enhancement, and compares it with HOG+SVM image recognition algorithm and deep learning algorithms such as Alexnet and FashionNet. The experimental results show that the proposed algorithm can effectively improve the recognition rate of clothing.

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Cited By

Tena SHartanto RArdiyanto I(2023)Content-Based Image Retrieval for Traditional Indonesian Woven Fabric Images Using a Modified Convolutional Neural Network MethodJournal of Imaging10.3390/jimaging90801659:8(165)Online publication date: 18-Aug-2023
https://doi.org/10.3390/jimaging9080165

Index Terms

Clothing Identification based on Fused Key Points
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
      1. Image processing

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cover image ACM Other conferences

ICIAI '19: Proceedings of the 2019 3rd International Conference on Innovation in Artificial Intelligence

March 2019

279 pages

ISBN:9781450361286

DOI:10.1145/3319921

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
University of Texas-Dallas: University of Texas-Dallas

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 March 2019

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ICIAI 2019

ICIAI 2019: 2019 The 3rd International Conference on Innovation in Artificial Intelligence

March 15 - 18, 2019

Suzhou, China

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Cited By

Tena SHartanto RArdiyanto I(2023)Content-Based Image Retrieval for Traditional Indonesian Woven Fabric Images Using a Modified Convolutional Neural Network MethodJournal of Imaging10.3390/jimaging90801659:8(165)Online publication date: 18-Aug-2023
https://doi.org/10.3390/jimaging9080165

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