Special Issue "Detection and Tracking of Targets in Forward-Looking InfraRed (FLIR) Imagery"


A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 15 May 2014

Special Issue Editors

Guest Editor
Prof. Dr. Andrea Sanna
Dipartimento di Automatica e Informatica Politecnico di Torino Corso Duca degli Abruzzi 24 I-10129 Torino, Italy
Website: https://didattica.polito.it/pls/portal30/sviluppo.scheda_pers_swas.show?m=3051
E-Mail: andrea.sanna@polito.it
Phone: +39 011 0907035
Interests: image processing; scientific visualization; virtual and augmented reality; human-computer interaction

Guest Editor
Prof. Dr. Fabrizio Lamberti
Dipartimento di Automatica e Informatica Politecnico di Torino Corso Duca degli Abruzzi 24 I-10129 Torino, Italy
Website: https://didattica.polito.it/pls/portal30/sviluppo.scheda_pers_swas.show?m=4174
E-Mail: fabrizio.lamberti@polito.it
Phone: +39 011 0907193
Interests: computer graphics; computer vision; image processing; human-computer interaction; digital arithmetic; intelligent information processing

Special Issue Information

Dear Colleagues,

Detection and tracking of targets in forward looking infrared (FLIR) imagery are challenging tasks. IR sensors often provide low signal-to-noise ratio and heavy background cluttering images. Non-stationary cameras can introduce further challenges, because detection and tracking might make it necessary to properly deal with sensor ego-motion through suitable estimation and compensation techniques. Moreover, further issues are posed by imagery with multiple and possibly moving target and non-target objects, which can blend into the background, change their signature, size, shape, and even overlap during their motion. Finally, specific applications could introduce cumbersome real-time constraints, thus requiring tracking techniques with a reduced computational footprint.

The objective of this Special Issue is to invite high state-of-the-art research contributions, tutorials, and position papers that address the broad challenges faced in analysis and processing of FLIR imagery. Original papers describing completed and unpublished work that are not currently under review by any other journal/magazine/conference/special issue are solicited.

Prof. Dr. Andrea Sanna
Prof. Dr. Fabrizio Lamberti
Guest Editors


Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed Open Access monthly journal published by MDPI.

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  • video surveillance
  • tracking and detection of pedestrians
  • autonomous vehicles
  • environmental monitoring
  • ego-motion compensation and background removal techniques
  • template-matching algorithms
  • deformable part models
  • automatic detection, recognition and identification of targets
  • real-time target tracking in military scenarios
  • applications and case studies

Published Papers (2 papers)

Sensors 2014, 14(4), 6666-6676; doi:10.3390/s140406666
Received: 14 March 2014; in revised form: 2 April 2014 / Accepted: 4 April 2014 / Published: 10 April 2014
Show/Hide Abstract | Download PDF Full-text (420 KB)
abstract graphic

Sensors 2014, 14(2), 3690-3701; doi:10.3390/s140203690
Received: 17 December 2013; in revised form: 13 February 2014 / Accepted: 14 February 2014 / Published: 21 February 2014
Show/Hide Abstract | Download PDF Full-text (665 KB) | View HTML Full-text | Download XML Full-text
abstract graphic

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Type of Paper: Article
Title: Target Tracking, Recognition and Segmentation in FLIR Imagery via Shape-aware Level Set
Author: Jiulu Gong, Guoliang Fan, Liangjiang Yu, Joseph P. Havlicek, Derong Chen and Ningjun Fan
Affiliation: School of Electrical and Computer Engineering Oklahoma State University Stillwater, OK 74078-5032, USA
Abstract: We propose a new integrated target tracking, recognition and segmentation algorithm, called ATR-Seg. An important component of ATR-Seg is a probabilistic shape-aware level set framework that incorporates a joint view-identity manifold (JVIM) for target shape modeling. As a shape generative model, JVIM features a unified manifold structure in the latent space that is embedded with one view-independent identity manifold and infinite identity- dependent view manifolds. In the ATR-Seg algorithm, the problem formulated as a sequential level-set optimization process over the latent space of JVIM, so that tracking and recognition can be jointly optimized via implicit shape matching where target segmentation is achieved as a by-product without any pre-processing and feature extraction. Experimental results on the recently released SENSIAC ATR database demonstrate the advantages and effective of ATR-Seg over two recent tracking techniques.

Last update: 30 December 2013

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