A Clothes Classification Method Based on the gcForest

In this paper, we propose a clothes classification method, an application of the gcForest. The gcForest, a novel decision tree ensemble method proposed by Zhou and Feng, performs excellently in many experiments. Moreover, we come up with some adjustment approaches for gcForest. Using these adjustment approaches, we get a satisfactory result when gcForest is used for clothes classification task. Furthermore, we create a data set for clothes classification which contains 8 categories of clothes including a total of 52000 images. And we preprocess the images in the data set by GrabCut-based clothes extraction algorithm.

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

[2]  Andrew Blake,et al.  "GrabCut" , 2004, ACM Trans. Graph..

[3]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[4]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[5]  Yann LeCun,et al.  Convolutional neural networks applied to house numbers digit classification , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[6]  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).

[7]  Javier Lorenzo-Navarro,et al.  Evaluation of LBP and HOG Descriptors for Clothing Attribute Description , 2014, VAAM@ICPR.

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

[9]  Tamara L. Berg,et al.  Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items , 2013, 2013 IEEE International Conference on Computer Vision.

[10]  Hanqing Lu,et al.  Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  J. An,et al.  Keyword extraction for text categorization , 2005, Proceedings of the 2005 International Conference on Active Media Technology, 2005. (AMT 2005)..

[12]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[13]  Gareth Funka-Lea,et al.  Graph Cuts and Efficient N-D Image Segmentation , 2006, International Journal of Computer Vision.

[14]  Ji Feng,et al.  Deep Forest: Towards An Alternative to Deep Neural Networks , 2017, IJCAI.