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Multimedia Tools and Applications

, Volume 77, Issue 24, pp 32179–32211 | Cite as

Accumulative image categorization: a personal photo classification method for progressive collection

  • Jiagao Hu
  • Zhengxing Sun
  • Yunhan Sun
  • Jinlong Shi
Article

Abstract

With the explosive growth of personal photos, an effective classification tool is becoming an urgent need to organize our progressive image collections. Facing the dynamically growing collections, we present a new method to categorize images effectively by integrating image clustering, incremental updating and user feedback together in an online framework. Considering the user burden and the user-specific preference during image classification, we propose several strategies to learn a customized classification model progressively for each user. Firstly, we use a multi-view learning method to learn the preferred classification perspective of the user. Secondly, we cluster similar images into groups according to user’s preference, so that images in a group can be categorized simultaneously with high efficiency. Thirdly, we propose a multi-centroid nearest class mean classifier to online learn the user’s preferred category granularity, and use it to classify the image groups. Unlike offline systems where pre-labeling and batch training often take hours or even days to perform, our approach is fully online. It can learn the classification model and classify newly acquired images alternately in no time. The sufficient experimental results and a user study demonstrate the effectiveness of the proposed method.

Keywords

Image classification Online learning Image clustering Nearest class mean classifier Progressive collection 

Notes

Acknowledgements

This work is supported by National High Technology Research and Development Program of China (No. 2007AA01Z334); National Natural Science Foundation of China (No. 61321491, 61272219); Innovation Fund of State Key Laboratory for Novel Software Technology (No. ZZKT2013A12, ZZKT2016A11); Program for New Century Excellent Talents in University of China (No. NCET-04-04605); Nanjing University Innovation and Creative Program for PhD candidate (No. 2016013).

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Authors and Affiliations

  1. 1.State Key Lab for Novel Software TechnologyNanjing UniversityNanjingChina
  2. 2.School of Computer Science and EngineeringJiangsu University of Science and TechnologyZhenjiangChina

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