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

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 necessa...

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Bibliographic Details
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2015
Subjects:
Online Access:Open Access: DOAB, download the publication
Open Access: DOAB: description of the publication
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720 1 |a Andrea Sanna (Ed.)  |4 aut 
720 1 |a Fabrizio Lamberti (Ed.)  |4 aut 
245 0 0 |a Detection and Tracking of Targets in Forward-Looking InfraRed (FLIR) Imagery 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2015 
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520 |a 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 Original papers describing completed and unpublished work that are not currently under review by any other journal/magazine/conference/special issue are solicited. 
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546 |a English 
653 |a applications and case studies 
653 |a automatic detection 
653 |a autonomous vehicles 
653 |a deformable part models 
653 |a ego-motion compensation and background removal techniques 
653 |a environmental monitoring 
653 |a real-time target tracking in military scenarios 
653 |a recognition and identification of targets 
653 |a template-matching algorithms 
653 |a tracking and detection of pedestrians 
653 |a video surveillance 
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