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A Thermal Object Tracking Benchmark
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, Tekniska fakulteten.ORCID-id: 0000-0002-6096-3648
2015 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Short-term single-object (STSO) tracking in thermal images is a challenging problem relevant in a growing number of applications. In order to evaluate STSO tracking algorithms on visual imagery, there are de facto standard benchmarks. However, we argue that tracking in thermal imagery is different than in visual imagery, and that a separate benchmark is needed. The available thermal infrared datasets are few and the existing ones are not challenging for modern tracking algorithms. Therefore, we hereby propose a thermal infrared benchmark according to the Visual Object Tracking (VOT) protocol for evaluation of STSO tracking methods. The benchmark includes the new LTIR dataset containing 20 thermal image sequences which have been collected from multiple sources and annotated in the format used in the VOT Challenge. In addition, we show that the ranking of different tracking principles differ between the visual and thermal benchmarks, confirming the need for the new benchmark.

Ort, förlag, år, upplaga, sidor
IEEE , 2015.
Nationell ämneskategori
Datorseende och robotik (autonoma system)
Identifikatorer
URN: urn:nbn:se:liu:diva-121001DOI: 10.1109/AVSS.2015.7301772ISI: 000380619700052ISBN: 978-1-4673-7632-7 (tryckt)OAI: oai:DiVA.org:liu-121001DiVA, id: diva2:850688
Konferens
12th IEEE International Conference on Advanced Video- and Signal-based Surveillance, Karlsruhe, Germany, August 25-28 2015
Tillgänglig från: 2015-09-02 Skapad: 2015-09-02 Senast uppdaterad: 2019-10-23Bibliografiskt 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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Berg, AmandaAhlberg, JörgenFelsberg, Michael

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