NDLI: Dynamic texture classification using dynamic fractal analysis

Content Provider	IEEE Xplore Digital Library
Author	Yong Xu Yuhui Quan Haibin Ling Hui Ji
Copyright Year	2011
Description	Author affiliation: Department of Mathematics, National University of Singapore, Singapore 117542 (Hui Ji) \|\| School of Computer Science & Engineering, South China Univ. of Tech., Guangzhou 510006, China (Yong Xu; Yuhui Quan) \|\| Department of Computer and Information Sciences, Temple University, Philadelphia, 19122, U.S.A. (Haibin Ling)
Abstract	In this paper, we developed a novel tool called dynamic fractal analysis for dynamic texture (DT) classification, which not only provides a rich description of DT but also has strong robustness to environmental changes. The resulting dynamic fractal spectrum (DFS) for DT sequences consists of two components: One is the volumetric dynamic fractal spectrum component (V-DFS) that captures the stochastic self-similarities of DT sequences as 3D volume datasets; the other is the multi-slice dynamic fractal spectrum component (S-DFS) that encodes fractal structures of DT sequences on 2D slices along different views of the 3D volume. Various types of measures of DT sequences are collected in our approach to analyze DT sequences from different perspectives. The experimental evaluation is conducted on three widely used benchmark datasets. In all the experiments, our method demonstrated excellent performance in comparison with state-of-the-art approaches.
Starting Page	1219
Ending Page	1226
File Size	1546018
Page Count	8
File Format	PDF
ISBN	9781457711015
ISSN	15505499
e-ISBN	9781457711022
DOI	10.1109/ICCV.2011.6126372
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-06
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fractals Three dimensional displays Vectors Dynamics Stochastic processes Video sequences Brightness
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Action Classification with Locality-Constrained Linear Coding

Concurrent Action Detection with Structural Prediction

Bags of Spacetime Energies for Dynamic Scene Recognition

Modeling 4D Human-Object Interactions for Event and Object Recognition

Extracting a fluid dynamic texture and the background from video

A Factorization Approach for Activity Recognition

Locally Invariant Fractal Features for Statistical Texture Classification

SphereFlow: 6 DoF Scene Flow from RGB-D Pairs

Viewpoint Invariant Texture Description Using Fractal Analysis

Dynamic texture classification using dynamic fractal analysis

Similar Documents

Action Classification with Locality-Constrained Linear Coding

Concurrent Action Detection with Structural Prediction

Bags of Spacetime Energies for Dynamic Scene Recognition

Modeling 4D Human-Object Interactions for Event and Object Recognition

Extracting a fluid dynamic texture and the background from video

A Factorization Approach for Activity Recognition

Locally Invariant Fractal Features for Statistical Texture Classification

SphereFlow: 6 DoF Scene Flow from RGB-D Pairs

Viewpoint Invariant Texture Description Using Fractal Analysis

Dynamic texture classification using dynamic fractal analysis