Evaluation of LBP and HOG Descriptors for Clothing Attribute Description

In this work an experimental study about the capability of the LBP, HOG descriptors and color for clothing attribute classification is presented. Two different variants of the LBP descriptor are considered, the original LBP and the uniform LBP. Two classifiers, Linear SVM and Random Forest, have been included in the comparison because they have been frequently used in clothing attributes classification. The experiments are carried out with a public available dataset, the clothing attribute dataset, that has 26 attributes in total. The obtained accuracies are over 75 % in most cases, reaching 80 % for the necktie or sleeve length attributes.

[1]  Fabio Roli,et al.  People Search with Textual Queries About Clothing Appearance Attributes , 2014, Person Re-Identification.

[2]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[3]  Yi Yang,et al.  Articulated pose estimation with flexible mixtures-of-parts , 2011, CVPR 2011.

[4]  Shaogang Gong,et al.  Person Re-Identification , 2014 .

[5]  Ming Yang,et al.  Real-time clothing recognition in surveillance videos , 2011, 2011 18th IEEE International Conference on Image Processing.

[6]  Matthieu Guillaumin,et al.  Segmentation Propagation in ImageNet , 2012, ECCV.

[7]  Josep Lladós,et al.  High-Level Clothes Description Based on Colour-Texture and Structural Features , 2003, IbPRIA.

[8]  Shuicheng Yan,et al.  Fashion Parsing With Weak Color-Category Labels , 2014, IEEE Transactions on Multimedia.

[9]  Matti Pietikäinen,et al.  Computer Vision Using Local Binary Patterns , 2011, Computational Imaging and Vision.

[10]  Rainer Stiefelhagen,et al.  Part-based clothing segmentation for person retrieval , 2011, 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).

[11]  Simone Calderara,et al.  A complete system for garment segmentation and color classification , 2013, Machine Vision and Applications.

[12]  Matti Pietikäinen,et al.  Face Analysis Using Local Binary Patterns , 2008 .

[13]  Huizhong Chen,et al.  Describing Clothing by Semantic Attributes , 2012, ECCV.

[14]  Luis E. Ortiz,et al.  Parsing clothing in fashion photographs , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Yannis Kalantidis,et al.  Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos , 2013, ICMR.

[16]  Luc Van Gool,et al.  Apparel Classification with Style , 2012, ACCV.

[17]  Liang-Gee Chen,et al.  Interactive clothing retrieval system , 2014, 2014 IEEE International Conference on Consumer Electronics (ICCE).

[18]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[19]  Tsuhan Chen,et al.  Clothing cosegmentation for recognizing people , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Meng Wang,et al.  Predicting occupation via human clothing and contexts , 2011, 2011 International Conference on Computer Vision.