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Channel Coded Distribution Field Tracking for Thermal Infrared Imagery
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.ORCID-id: 0000-0002-6591-9400
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.ORCID-id: 0000-0002-6763-5487
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-6096-3648
2016 (Engelska)Ingår i: PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016), IEEE , 2016, s. 1248-1256Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

We address short-term, single-object tracking, a topic that is currently seeing fast progress for visual video, for the case of thermal infrared (TIR) imagery. The fast progress has been possible thanks to the development of new template-based tracking methods with online template updates, methods which have not been explored for TIR tracking. Instead, tracking methods used for TIR are often subject to a number of constraints, e.g., warm objects, low spatial resolution, and static camera. As TIR cameras become less noisy and get higher resolution these constraints are less relevant, and for emerging civilian applications, e.g., surveillance and automotive safety, new tracking methods are needed. Due to the special characteristics of TIR imagery, we argue that template-based trackers based on distribution fields should have an advantage over trackers based on spatial structure features. In this paper, we propose a template-based tracking method (ABCD) designed specifically for TIR and not being restricted by any of the constraints above. In order to avoid background contamination of the object template, we propose to exploit background information for the online template update and to adaptively select the object region used for tracking. Moreover, we propose a novel method for estimating object scale change. The proposed tracker is evaluated on the VOT-TIR2015 and VOT2015 datasets using the VOT evaluation toolkit and a comparison of relative ranking of all common participating trackers in the challenges is provided. Further, the proposed tracker, ABCD, and the VOT-TIR2015 winner SRDCFir are evaluated on maritime data. Experimental results show that the ABCD tracker performs particularly well on thermal infrared sequences.

Ort, förlag, år, upplaga, sidor
IEEE , 2016. s. 1248-1256
Serie
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, ISSN 2160-7508
Nationell ämneskategori
Datorseende och robotik (autonoma system)
Identifikatorer
URN: urn:nbn:se:liu:diva-134402DOI: 10.1109/CVPRW.2016.158ISI: 000391572100151ISBN: 978-1-5090-1438-5 (tryckt)ISBN: 978-1-5090-1437-8 (digital)OAI: oai:DiVA.org:liu-134402DiVA, id: diva2:1072885
Konferens
Computer Vision and Pattern Recognition Workshops (CVPRW), 2016 IEEE Conference on
Forskningsfinansiär
Vetenskapsrådet, D0570301EU, FP7, Sjunde ramprogrammet, 312784EU, FP7, Sjunde ramprogrammet, 607567Tillgänglig från: 2017-02-09 Skapad: 2017-02-09 Senast uppdaterad: 2018-01-13
Ingår i avhandling
1. Detection and Tracking in Thermal Infrared Imagery
Öppna denna publikation i ny flik eller fönster >>Detection and Tracking in Thermal Infrared Imagery
2016 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Thermal cameras have historically been of interest mainly for military applications. Increasing image quality and resolution combined with decreasing price and size during recent years have, however, opened up new application areas. They are now widely used for civilian applications, e.g., within industry, to search for missing persons, in automotive safety, as well as for medical applications. Thermal cameras are useful as soon as it is possible to measure a temperature difference. Compared to cameras operating in the visual spectrum, they are advantageous due to their ability to see in total darkness, robustness to illumination variations, and less intrusion on privacy.

This thesis addresses the problem of detection and tracking in thermal infrared imagery. Visual detection and tracking of objects in video are research areas that have been and currently are subject to extensive research. Indications oftheir popularity are recent benchmarks such as the annual Visual Object Tracking (VOT) challenges, the Object Tracking Benchmarks, the series of workshops on Performance Evaluation of Tracking and Surveillance (PETS), and the workshops on Change Detection. Benchmark results indicate that detection and tracking are still challenging problems.

A common belief is that detection and tracking in thermal infrared imagery is identical to detection and tracking in grayscale visual imagery. This thesis argues that the preceding allegation is not true. The characteristics of thermal infrared radiation and imagery pose certain challenges to image analysis algorithms. The thesis describes these characteristics and challenges as well as presents evaluation results confirming the hypothesis.

Detection and tracking are often treated as two separate problems. However, some tracking methods, e.g. template-based tracking methods, base their tracking on repeated specific detections. They learn a model of the object that is adaptively updated. That is, detection and tracking are performed jointly. The thesis includes a template-based tracking method designed specifically for thermal infrared imagery, describes a thermal infrared dataset for evaluation of template-based tracking methods, and provides an overview of the first challenge on short-term,single-object tracking in thermal infrared video. Finally, two applications employing detection and tracking methods are presented.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2016. s. 66
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1744
Nyckelord
thermal, infrared, detection, tracking
Nationell ämneskategori
Datorseende och robotik (autonoma system)
Identifikatorer
urn:nbn:se:liu:diva-126955 (URN)10.3384/lic.diva-126955 (DOI)978-91-7685-789-2 (ISBN)
Presentation
2016-05-10, Visionen, Hus B, Campus Valla, Linköpings universitet, Linköping, 16:16 (Engelska)
Opponent
Handledare
Forskningsfinansiär
Vetenskapsrådet, D0570301EU, FP7, Sjunde ramprogrammet, 312784EU, FP7, Sjunde ramprogrammet, 607567
Tillgänglig från: 2016-04-11 Skapad: 2016-04-08 Senast uppdaterad: 2018-01-10Bibliografiskt granskad

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Berg, AmandaAhlberg, JörgenFelsberg, Michael
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