NDLI: Hybrid multiple-object tracker incorporating Particle Swarm Optimization and Particle Filter

Content Provider	IEEE Xplore Digital Library
Author	Chen-Chien Hsu Yung-Ching Chu Ming-Chih Lu
Copyright Year	2013
Description	Author affiliation: Dept. of Appl. Electron. Technol., Nat. Taiwan Normal Univ., Taipei, Taiwan (Chen-Chien Hsu; Yung-Ching Chu) \|\| Dept. of Electron. Eng., St. John's Univ., Taipei, Taiwan (Ming-Chih Lu)
Abstract	This study presents a hybrid algorithm incorporating Particle Swarm Optimization (PSO) and Particle Filter (PF) for multiple-object tracking based mainly on gray-level histogram model. To start with, the hybrid object tracker uses PSO to search the objects in the beginning, taking advantage of the PSO for global optimization. Once the objects have been successfully found by PSO, the hybrid object tracker then switches to PF to continuously track the objects. To avoid the varying-size problem of the objects, Speeded Up Robust Features (SURF) is used to detect the object around its neighborhood in the video sequence for defining the real image size of the object for remodeling the target object by histogram. As a result, tracking speed can be maintained by the hybrid tracker using simple histogram model while circumventing the varying-size problem of the objects during the tracking process.
Starting Page	189
Ending Page	193
File Size	461040
Page Count	5
File Format	PDF
ISBN	9781479900077
ISSN	23250925
e-ISBN	9781479900091
DOI	10.1109/ICSSE.2013.6614657
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-04
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Computer vision Target tracking Search problems Particle filters Object tracking Particle swarm optimization
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 categorized particle swarm optimization for object tracking

Video Object Tracking Based on Swarm Optimized Particle Filter

Adaptive block-fusion multiple feature tracking in a particle filter framework

A particle filter for joint detection and tracking of multiple objects in color video sequences

Video object tracking based on swarm optimized particle filter

Object Tracking Based on Particle Filter with Multi-scale Mode

A hybrid Particle Swarm Optimization with cooperative method for multi-object tracking

Object tracking via Modified CamShift in Sequential Bayesian Filtering Framework

Particle Swarm Optimized Unscented Particle Filter for Target Tracking

Hybrid multiple-object tracker incorporating Particle Swarm Optimization and Particle Filter

Similar Documents

A categorized particle swarm optimization for object tracking

Video Object Tracking Based on Swarm Optimized Particle Filter

Adaptive block-fusion multiple feature tracking in a particle filter framework

A particle filter for joint detection and tracking of multiple objects in color video sequences

Video object tracking based on swarm optimized particle filter

Object Tracking Based on Particle Filter with Multi-scale Mode

A hybrid Particle Swarm Optimization with cooperative method for multi-object tracking

Object tracking via Modified CamShift in Sequential Bayesian Filtering Framework

Particle Swarm Optimized Unscented Particle Filter for Target Tracking

Hybrid multiple-object tracker incorporating Particle Swarm Optimization and Particle Filter