Experiments on Selection of Codebooks for Local Image Feature Histograms

Authors:
Ville Viitaniemi;Jorma Laaksonen
Affiliations:
Department of Information and Computer Science, Helsinki University of Technology, TKK, Finland FI-02015;Department of Information and Computer Science, Helsinki University of Technology, TKK, Finland FI-02015
Venue:
VISUAL '08 Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management
Year:
2008

Citing 7
Cited 7

Pattern recognition: statistical, structural and neural approaches

Pattern recognition: statistical, structural and neural approaches
Self-Organizing Maps

Self-Organizing Maps
Video Google: A Text Retrieval Approach to Object Matching in Videos

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Scale & Affine Invariant Interest Point Detectors

International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study

International Journal of Computer Vision
Improving the accuracy of global feature fusion based image categorisation

SAMT'07 Proceedings of the semantic and digital media technologies 2nd international conference on Semantic Multimedia

Combining Local Feature Histograms of Different Granularities

SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Representing Images with Χ2 Distance Based Histograms of SIFT Descriptors

ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Region matching techniques for spatial bag of visual words based image category recognition

ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
Color-Aware local spatiotemporal features for action recognition

CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
A visual approach for video geocoding using bag-of-scenes

Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Domain-specific image geocoding: a case study on Virginia tech building photos

Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Visual word spatial arrangement for image retrieval and classification

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

Histograms of local features have proven to be powerful representations in image classification and object detection. In this paper we experimentally compare techniques for selecting histogram codebooks for the purpose of classifying 5000 images of PASCAL NoE VOC Challenge 2007 collection. We study some well-known unsupervised clustering algorithms in the task of histogram codebook generation when the classification is performed in post-supervised fashion on basis of histograms of interest point SIFT features. We also consider several methods for supervised codebook generation that exploit the knowledge of the image classes to be detected already when selecting the histogram bins.