Object-based Image Classification and Object Detection

Object-based Image Classification and Object Detection

Shuai Zheng1    Junge Zhang1   Yinan Yu Yongzhen Huang Weiqiang Ren1, Kaiqi Huang1, Tieniu Tan1

1NLPR, Institute of Automation, Chinese Academy of Sciences

Abstract

Built on the top of deformable part based model, an very exhausted feature learning and ensemble learning research has been conducted to push part-based method to the performance limits.

PASCAL VOC Challenge provides a platform to evaluate how object based image classification and object detection work on the real image data(e.g. Flickr images). The challenge database contains 20 classes of object. All the image are collected from Flickr public available images. The purpose of image classification is to identify the class label of the objects in given an image. Based on the existing state-of-the-art Bag-of-words framework, we improved it by developing three new components including saliency coding, code relation modeling, and dictionary learning. Insipired by the existing state-of-the-art deformable part based model framework, we develop an efficient but complicated approaches to achieve both low-level feature combinations and high-level hybrid approach combinations. Recently, some new improvements leads NLPR to win the two tasks object detection and image classification at PASCAL VOC Challenge 2011 again.Find more information at PASCAL VOC Challenge website. link.

Overview diagram of the object detection approach

Overview Summary of object based image classification approach

Results of Detection at VOC 2010

Duration:

Jan,2010-July, 2012

Publications and Presentations

Y. Yu, J. Zhang, Y. Huang, S. Zheng, W. Ren, K. Huang, and T. Tan, “Object Detection by Context and Boosted HOG-LBP“, in PASCAL Visual Object Challenge Workshop, European Conference on Computer Vision (ECCV), Crete, Greece, 2010.(No.1) [bib]

Y. Huang, S. Zheng, W. Ren, Y. Yu, J. Zhang, K. Huang, and T. Tan, “SVM classifier and saliency coding for Image classification“, in PASCAL Visual Object Challenge Workshop, European Conference on Computer Vision (ECCV), Crete, Greece, 2010.

J. Zhang, Y. Yu, S. Zheng, K. Huang, and T. Tan, “An Empirical Study of Visual Features for Part Based Model,” in Asian Conference on Pattern Recognition (ACPR), Beijing, China, 2011. [bib]

Software

Efficient Implementation of Bag of words [code]

Links

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