Supervised local sparse coding of sub-image features for image retrieval

Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

The success of sparse representations in image modeling and recovery has motivated its use in computer vision applications. Image retrieval and classification tasks require extracting features that discriminate different image classes. State-of-the-art object recognition methods based on sparse coding use spatial pyramid features obtained from dense descriptors. In this paper, we develop a feature extraction method that uses multiple global/local features extracted from large overlapping regions of an image, which we refer to as sub-images. We propose a procedure for dictionary design and supervised local sparse coding of sub-image heterogeneous features. We perform image retrieval on the Microsoft Research Cambridge image dataset and show that the proposed features outperform the spatial pyramid features obtained using dense descriptors.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages3117-3120
Number of pages4
DOIs
StatePublished - Dec 1 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Publication series

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

Other

Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
CountryUnited States
CityLake Buena Vista, FL
Period9/30/1210/3/12

Keywords

  • Local linear modeling
  • Sparse coding
  • dictionary learning
  • image retrieval

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Thiagarajan, J. J., Natesan Ramamurthy, K., Sattigeri, P., & Spanias, A. (2012). Supervised local sparse coding of sub-image features for image retrieval. In 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings (pp. 3117-3120). [6467560] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2012.6467560