NDLI: Model based video segmentation

Content Provider	IEEE Xplore Digital Library
Author	Dalong Li Hanqing Lu
Copyright Year	2000
Description	Author affiliation: Inst. of Autom., Acad. Sinica, China (Dalong Li)
Abstract	With the fast growth of video resources, efficient video classification and management are becoming more and more important. Video partitioning is a key issue in video classification. The video partitioning involves the detection of boundaries between uninterrupted segments (video shots) of scenes. Shot boundaries can be classified into two categories, gradual transition and instantaneous change (called camera break). Detection of a gradual transition is considered to be difficult. Block-based image comparison was proposed to detect shot boundaries. Unfortunately, if the differences of the corresponding blocks in the images are measured by gray levels, the method will make false alarms when the gray level change suddenly due to reasons other than shot shifts such as illumination variation which is common in news video. What is more, the step-variable algorithm can not distinguish wipe and dissolve. It is likely that step-variable algorithm will make false alarms of gradual transitions. In this paper, the proposed algorithm named MVS (model based video segmentation) can distinguish illumination variation from camera breaks as well as wipe from dissolve. Moreover, the positions of the gradual transition are located correctly. MVS is especially efficient in detecting wipes. Experimental results are reported in the paper to validate the proposed method.
Starting Page	120
Ending Page	129
File Size	554148
Page Count	10
File Format	PDF
ISBN	0780364880
ISSN	15206130
DOI	10.1109/SIPS.2000.886710
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-10-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Gunshot detection systems Layout Lighting Change detection algorithms Histograms Automation Resource management Image segmentation Partitioning algorithms
Content Type	Text
Resource Type	Article

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

A novel approach to scene change detection using a cross entropy

Lighting change problem in shot detection

Video partitioning and camera motion characterization for content-based video indexing

Fast feature-based video segmentation and annotation

Temporal Video Segmentation by Graph Partitioning

Video segmentation based on sequential change detection

Scene abrupt change detection

Video segmentation using a histogram-based fuzzy c-means clustering algorithm

Gradual transition detection based on bipartite graph matching approach

Model based video segmentation

Similar Documents

A novel approach to scene change detection using a cross entropy

Lighting change problem in shot detection

Video partitioning and camera motion characterization for content-based video indexing

Fast feature-based video segmentation and annotation

Temporal Video Segmentation by Graph Partitioning

Video segmentation based on sequential change detection

Scene abrupt change detection

Video segmentation using a histogram-based fuzzy c-means clustering algorithm

Gradual transition detection based on bipartite graph matching approach

Model based video segmentation