Sparse representation based visual element analysis

Xue Li; Hongxun Yao; Xiaoshuai Sun; Rongrong Ji; Xianming Liu; Pengfei Xu

doi:10.1109/ICIP.2011.6116637

Sparse representation based visual element analysis

Xue Li
, Hongxun Yao^*
, Xiaoshuai Sun
, Rongrong Ji
, Xianming Liu
, Pengfei Xu

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Modern clothes are designed based on various visual elements of different fashion styles. Traditional vision-based clothes recommendation methods focused on searching clothes which are similar with user preferred samples in the aspects of colors and partial shape elements. In this paper, we propose a method of recommending clothes by mining visual elements of different fashion styles. Independent Component Analysis (ICA) is employed to extract sparse features, and then Term-Frequency (TF) analysis is applied to discover visual elements from these independent components. Finally, we test three ranking metrics for clothes recommendation including Euclidian distance of TFs, Cosine distance of TFs and Minimum TF. Experimental results based on web commercial images demonstrate the effectiveness of the proposed method.

Original language	English
Title of host publication	ICIP 2011
Subtitle of host publication	2011 18th IEEE International Conference on Image Processing
Pages	657-660
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2011.6116637
State	Published - 2011
Externally published	Yes
Event	2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium Duration: 11 Sep 2011 → 14 Sep 2011

Publication series

Name	Proceedings - International Conference on Image Processing, ICIP
ISSN (Print)	1522-4880

Conference

Conference	2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/Territory	Belgium
City	Brussels
Period	11/09/11 → 14/09/11

Keywords

Clothes recommendation
independent component analysis
style mining
term frequency

Access to Document

10.1109/ICIP.2011.6116637

Cite this

@inproceedings{2543b770da4a4f0b9363e87c2adfb278,

title = "Sparse representation based visual element analysis",

abstract = "Modern clothes are designed based on various visual elements of different fashion styles. Traditional vision-based clothes recommendation methods focused on searching clothes which are similar with user preferred samples in the aspects of colors and partial shape elements. In this paper, we propose a method of recommending clothes by mining visual elements of different fashion styles. Independent Component Analysis (ICA) is employed to extract sparse features, and then Term-Frequency (TF) analysis is applied to discover visual elements from these independent components. Finally, we test three ranking metrics for clothes recommendation including Euclidian distance of TFs, Cosine distance of TFs and Minimum TF. Experimental results based on web commercial images demonstrate the effectiveness of the proposed method.",

keywords = "Clothes recommendation, independent component analysis, style mining, term frequency",

author = "Xue Li and Hongxun Yao and Xiaoshuai Sun and Rongrong Ji and Xianming Liu and Pengfei Xu",

year = "2011",

doi = "10.1109/ICIP.2011.6116637",

language = "英语",

isbn = "9781457713033",

series = "Proceedings - International Conference on Image Processing, ICIP",

pages = "657--660",

booktitle = "ICIP 2011",

note = "2011 18th IEEE International Conference on Image Processing, ICIP 2011 ; Conference date: 11-09-2011 Through 14-09-2011",

}

Li, X, Yao, H, Sun, X, Ji, R, Liu, X & Xu, P 2011, Sparse representation based visual element analysis. in ICIP 2011: 2011 18th IEEE International Conference on Image Processing., 6116637, Proceedings - International Conference on Image Processing, ICIP, pp. 657-660, 2011 18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, 11/09/11. https://doi.org/10.1109/ICIP.2011.6116637

TY - GEN

T1 - Sparse representation based visual element analysis

AU - Li, Xue

AU - Yao, Hongxun

AU - Sun, Xiaoshuai

AU - Ji, Rongrong

AU - Liu, Xianming

AU - Xu, Pengfei

PY - 2011

Y1 - 2011

N2 - Modern clothes are designed based on various visual elements of different fashion styles. Traditional vision-based clothes recommendation methods focused on searching clothes which are similar with user preferred samples in the aspects of colors and partial shape elements. In this paper, we propose a method of recommending clothes by mining visual elements of different fashion styles. Independent Component Analysis (ICA) is employed to extract sparse features, and then Term-Frequency (TF) analysis is applied to discover visual elements from these independent components. Finally, we test three ranking metrics for clothes recommendation including Euclidian distance of TFs, Cosine distance of TFs and Minimum TF. Experimental results based on web commercial images demonstrate the effectiveness of the proposed method.

AB - Modern clothes are designed based on various visual elements of different fashion styles. Traditional vision-based clothes recommendation methods focused on searching clothes which are similar with user preferred samples in the aspects of colors and partial shape elements. In this paper, we propose a method of recommending clothes by mining visual elements of different fashion styles. Independent Component Analysis (ICA) is employed to extract sparse features, and then Term-Frequency (TF) analysis is applied to discover visual elements from these independent components. Finally, we test three ranking metrics for clothes recommendation including Euclidian distance of TFs, Cosine distance of TFs and Minimum TF. Experimental results based on web commercial images demonstrate the effectiveness of the proposed method.

KW - Clothes recommendation

KW - independent component analysis

KW - style mining

KW - term frequency

UR - https://www.scopus.com/pages/publications/84863032143

U2 - 10.1109/ICIP.2011.6116637

DO - 10.1109/ICIP.2011.6116637

M3 - 会议稿件

AN - SCOPUS:84863032143

SN - 9781457713033

T3 - Proceedings - International Conference on Image Processing, ICIP

SP - 657

EP - 660

BT - ICIP 2011

T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011

Y2 - 11 September 2011 through 14 September 2011

ER -

Sparse representation based visual element analysis

Abstract

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Conference

Keywords

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