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The Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge Results
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-6096-3648
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.
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Termisk Systemteknik AB, Linköping, Sweden.ORCID-id: 0000-0002-6763-5487
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2015 (Engelska)Ingår i: Proceedings of the IEEE International Conference on Computer Vision, Institute of Electrical and Electronics Engineers (IEEE), 2015, s. 639-651Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The Thermal Infrared Visual Object Tracking challenge 2015, VOTTIR2015, aims at comparing short-term single-object visual trackers that work on thermal infrared (TIR) sequences and do not apply prelearned models of object appearance. VOT-TIR2015 is the first benchmark on short-term tracking in TIR sequences. Results of 24 trackers are presented. For each participating tracker, a short description is provided in the appendix. The VOT-TIR2015 challenge is based on the VOT2013 challenge, but introduces the following novelties: (i) the newly collected LTIR (Linköping TIR) dataset is used, (ii) the VOT2013 attributes are adapted to TIR data, (iii) the evaluation is performed using insights gained during VOT2013 and VOT2014 and is similar to VOT2015.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE), 2015. s. 639-651
Serie
IEEE International Conference on Computer Vision. Proceedings, ISSN 1550-5499
Nationell ämneskategori
Datorseende och robotik (autonoma system)
Identifikatorer
URN: urn:nbn:se:liu:diva-126917DOI: 10.1109/ICCVW.2015.86ISI: 000380434700077ISBN: 978-146738390-5 (tryckt)OAI: oai:DiVA.org:liu-126917DiVA, id: diva2:917646
Konferens
IEEE International Conference on Computer Vision Workshop (ICCVW. 7-13 Dec. 2015 Santiago, Chile
Tillgänglig från: 2016-04-07 Skapad: 2016-04-07 Senast uppdaterad: 2018-01-10Bibliografiskt granskad
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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