NDLI: Multiple target detection and tracking by interacting joint probabilistic data association filter and bayesian networks: Application to real data

Content Provider	IEEE Xplore Digital Library
Author	Jida, B. Lherbier, R. Noyer, J.-C. Wahl, M.
Copyright Year	2009
Description	Author affiliation: Univ. Lille Nord de France, F-59000 Lille, France (Jida, B.; Lherbier, R.; Noyer, J.-C.; Wahl, M.)
Abstract	This paper proposes an algorithm of multiple target detection and tracking on road, developed for the laserscanner data. It is based on Bayesian networks for calculating the detection probability of target used in a JPDA filter. We propose a method based on the integration of detection probability of target in the JPDA filter, in which the joint probabilities of associations are calculated for multiple target. It then solves the problem of founding one or more observation in more than one gate of target by constructing hypothesis. A Bayesian network is used to determine this probability of detection. It includes a target model and takes into account the contextual information such as the size of the target, the distance between targets and the center of the sensor characteristics (position, measurement uncertainty). The method is applied to real data provided by a scanning laser sensor with multiple targets. as well as the possibility that an object enters and leaves the scene.
Starting Page	1
Ending Page	8
File Size	1636569
Page Count	8
File Format	PDF
ISBN	9781424455195
DOI	10.1109/ITSC.2009.5309828
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object detection Target tracking Filters Bayesian methods Probability Sensor phenomena and characterization Roads Context modeling Measurement uncertainty Laser modes JPDA filter Multiple Target Detection and Modeling bayesian networks occultation
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

Tracking multiple interacting targets using a joint probabilistic data association filter.

Improved Joint Probabilistic Data Association Filter for Multi-Target Tracking in Wireless Sensor Networks

Tracking of splitting targets in clutter using an interacting multiple model joint probabilistic data association filter

Cheap Joint Probabilistic Data Association Filters in an Interacting Multiple Model Design

Incorporating statistical background model and Joint Probabilistic Data Association filter into motorcycle tracking

Research on a new algorithm of target tracking

Improved Joint Probabilistic Data Association (JPDA) Filter Using Motion Feature for Multiple Maneuvering Targets in Uncertain Tracking Situations

Extended Kalman filtering and Interacting Multiple Model for tracking maneuvering targets in sensor netwotrks

Multiple target tracking using particle filter based multi-scan joint probabilistic data association filter

Multiple target detection and tracking by interacting joint probabilistic data association filter and bayesian networks: Application to real data

Similar Documents

Tracking multiple interacting targets using a joint probabilistic data association filter.

Improved Joint Probabilistic Data Association Filter for Multi-Target Tracking in Wireless Sensor Networks

Tracking of splitting targets in clutter using an interacting multiple model joint probabilistic data association filter

Cheap Joint Probabilistic Data Association Filters in an Interacting Multiple Model Design

Incorporating statistical background model and Joint Probabilistic Data Association filter into motorcycle tracking

Research on a new algorithm of target tracking

Improved Joint Probabilistic Data Association (JPDA) Filter Using Motion Feature for Multiple Maneuvering Targets in Uncertain Tracking Situations

Extended Kalman filtering and Interacting Multiple Model for tracking maneuvering targets in sensor netwotrks

Multiple target tracking using particle filter based multi-scan joint probabilistic data association filter

Multiple target detection and tracking by interacting joint probabilistic data association filter and bayesian networks: Application to real data