Detection of multiple dynamic textures using feature space mapping

Authors:
Ashfaqur Rahman;Manzur Murshed
Affiliations:
Department of Computer Science, American International University Bangladesh, Dhaka, Bangladesh and Monash University, Victoria, Australia;Gippsland School of Information Technology, Monash University, Churchill, Victoria
Venue:
IEEE Transactions on Circuits and Systems for Video Technology
Year:
2009

Citing 5
Cited 1

Dynamic Texture Segmentation

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Mixtures of Dynamic Textures

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Detecting regions of dynamic texture

SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Nonparametric motion characterization using causal probabilistic models for video indexing and retrieval

IEEE Transactions on Image Processing
A Temporal Texture Characterization Technique Using Block-Based Approximated Motion Measure

IEEE Transactions on Circuits and Systems for Video Technology

Change detection for temporal texture in the Fourier domain

ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Image sequences of smoke, fire, etc. are known as dynamic textures. Research is mostly limited to characterization of single dynamic textures. In this paper we address the problem of detecting the presence of multiple dynamic textures in an image sequence by establishing a correspondence between the feature space of dynamic textures and that of their mixture in an image sequence. Accuracy of our proposed technique is both analytically and empirically established with detection experiments yielding 92.5% average accuracy on a diverse set of dynamic texture mixtures in synthetically generated as well as real-world image sequences.