High-entropy layouts for content-based browsing and retrieval

Authors:
Ruixuan Wang;Stephen J. McKenna;Junwei Han
Affiliations:
University of Dundee, UK;University of Dundee, UK;University of Dundee, UK
Venue:
Proceedings of the ACM International Conference on Image and Video Retrieval
Year:
2009

Citing 7
Cited 1

VisualSEEk: a fully automated content-based image query system

MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
A Metric for Distributions with Applications to Image Databases

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Feature extraction by non parametric mutual information maximization

The Journal of Machine Learning Research
Visualization and User-Modeling for Browsing Personal Photo Libraries

International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Effective browsing of web image search results

Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Interactive access to large image collections using similarity-based visualization

Journal of Visual Languages and Computing
A novel approach to enable semantic and visual image summarization for exploratory image search

MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval

Learning Query-Dependent Distance Metrics for Interactive Image Retrieval

ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Multimedia browsing and retrieval systems can use dimensionality reduction methods to map from high-dimensional content-based feature distributions to low-dimensional layout spaces for visualization. However, this often results in displays in which many items are occluded whilst large regions are empty or only sparsely populated with items. Furthermore, such methods do not take into account the shape of the region of layout space to be populated. This paper proposes a layout method that addresses these limitations. Layout distributions with low Renyi quadratic entropy are penalized since these result in displays in which some regions are over-populated (i.e. many images are occluded), sparsely populated or empty. Experiments using two image datasets and a comparison with two related methods show the effectiveness of the proposed method.