NDLI: Object-based video segmentation using spatio-temporal energy

Content Provider	IEEE Xplore Digital Library
Author	Bao Hongqiang Zhang Zhaoyang
Copyright Year	2004
Description	Author affiliation: Sch. of Commun. & Inf. Eng., Shanghai Univ., China (Bao Hongqiang; Zhang Zhaoyang)
Abstract	Segmentation of moving object in a video sequence is one of the most challenging problems in video processing due to the complexity of its motion. This paper presents an approach of object segmentation with spatio-temporal energy. First, according to the dissimilar characteristic of the intra-frame and inter-frame (spatial and temporal) information, a novel energy model, which is based on Markov random fields and residual fields, is proposed. Then, an improved regions growing method is used to segment and label the image in inter-frame, and an object mask is achieved by the proposed spatio-temporal energy model, after morphology filter is adopted to get the better results, moving object are extracted. Finally, while the occlusion emerges due to overlapping motion between both objects, the covered/uncovered object could be identified by both the spatial and temporal energy which is rapidly changed in respect to the previous frame. The experiment results show that the approach is effective.
Starting Page	1260
Ending Page	1263
File Size	641317
Page Count	4
File Format	PDF
ISBN	0780384067
DOI	10.1109/ICOSP.2004.1441554
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-08-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Video sequences Object segmentation Markov random fields Videoconference Humans Real time systems Signal processing algorithms Potential energy Power engineering and energy Image segmentation
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

SPATIO-TEMPORAL SEGMENTATION AND REGIONS TRACKING OF HIGH DEFINITION VIDEO SEQUENCES USING A MARKOV RANDOM FIELD MODEL

Automatic video segmentation for MPEG-4 using predictive watershed

Multiple feature temporal models for object detection in video

Annoyance of spatio-temporal artifacts in segmentation quality assessment [video sequences]

Spatio-temporal segmentation and regions tracking of high definition video sequences based on a Markov Random Field model

Real-time segmentation of objects from video sequences with non-stationary backgrounds using spatio-temporal coherence

Non-rigid object segmentation in video sequences using Markov random field

Segmentation of Video Sequences using Spatial-temporal Conditional Random Fields

Efficient Probabilistic Spatio-Temporal Video Object Segmentation

Object-based video segmentation using spatio-temporal energy

Similar Documents

SPATIO-TEMPORAL SEGMENTATION AND REGIONS TRACKING OF HIGH DEFINITION VIDEO SEQUENCES USING A MARKOV RANDOM FIELD MODEL

Automatic video segmentation for MPEG-4 using predictive watershed

Multiple feature temporal models for object detection in video

Annoyance of spatio-temporal artifacts in segmentation quality assessment [video sequences]

Spatio-temporal segmentation and regions tracking of high definition video sequences based on a Markov Random Field model

Real-time segmentation of objects from video sequences with non-stationary backgrounds using spatio-temporal coherence

Non-rigid object segmentation in video sequences using Markov random field

Segmentation of Video Sequences using Spatial-temporal Conditional Random Fields

Efficient Probabilistic Spatio-Temporal Video Object Segmentation

Object-based video segmentation using spatio-temporal energy