| 1. |
- Ahlberg, Jörgen, 1971-, et al.
(författare)
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Evaluating Template Rescaling in Short-Term Single-Object Tracking
- 2015
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Konferensbidrag (refereegranskat)abstract
- In recent years, short-term single-object tracking has emerged has a popular research topic, as it constitutes the core of more general tracking systems. Many such tracking methods are based on matching a part of the image with a template that is learnt online and represented by, for example, a correlation filter or a distribution field. In order for such a tracker to be able to not only find the position, but also the scale, of the tracked object in the next frame, some kind of scale estimation step is needed. This step is sometimes separate from the position estimation step, but is nevertheless jointly evaluated in de facto benchmarks. However, for practical as well as scientific reasons, the scale estimation step should be evaluated separately – for example,theremightincertainsituationsbeothermethodsmore suitable for the task. In this paper, we describe an evaluation method for scale estimation in template-based short-term single-object tracking, and evaluate two state-of-the-art tracking methods where estimation of scale and position are separable.
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| 2. |
- Ahlberg, Jörgen, 1971-, et al.
(författare)
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Multi-person fever screening using a thermal and a visual camera
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We propose a system to automatically measure the body temperature of persons as they pass. In contrast to exisitng systems, the persons do not need to stop and look into a camera one-by-one. Instead, their eye corners are automatically detected and the temperatures therein measured using a thermal camera. The system handles multiple simultaneous persons and can thus be used where a flow of people pass, such as at airport gates.
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| 3. |
- Berg, Amanda, 1988-, et al.
(författare)
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A thermal infrared dataset for evaluation of short-term tracking methods
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- During recent years, thermal cameras have decreased in both size and cost while improving image quality. The area of use for such cameras has expanded with many exciting applications, many of which require tracking of objects. While being subject to extensive research in the visual domain, tracking in thermal imagery has historically been of interest mainly for military purposes. The available thermal infrared datasets for evaluating methods addressing these problems are few and the ones that do are not challenging enough for today’s tracking algorithms. Therefore, we hereby propose a thermal infrared dataset for evaluation of short-term tracking methods. The dataset consists of 20 sequences which have been collected from multiple sources and the data format used is in accordance with the Visual Object Tracking (VOT) Challenge.
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| 4. |
- Berg, Amanda, 1988-, et al.
(författare)
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A Thermal Object Tracking Benchmark
- 2015
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 5. |
- Berg, Amanda, 1988-, et al.
(författare)
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An Overview of the Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge
- 2016
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The Thermal Infrared Visual Object Tracking (VOT-TIR2015) Challenge was organized in conjunction with ICCV2015. It was the first benchmark on short-term,single-target tracking in thermal infrared (TIR) sequences. The challenge aimed at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. It was based on the VOT2013 Challenge, but introduced the following novelties: (i) the utilization of the LTIR (Linköping TIR) dataset, (ii) adaption of the VOT2013 attributes to thermal data, (iii) a similar evaluation to that of VOT2015. This paper provides an overview of the VOT-TIR2015 Challenge as well as the results of the 24 participating trackers.
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| 6. |
- Berg, Amanda, 1988-, et al.
(författare)
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Channel Coded Distribution Field Tracking for Thermal Infrared Imagery
- 2016
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Ingår i: PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016). - : IEEE. - 9781509014385 - 9781509014378 ; , s. 1248-1256
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 7. |
- Berg, Amanda, 1988-, et al.
(författare)
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Classification and temporal analysis of district heating leakages in thermal images
- 2014
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Ingår i: Proceedings of The 14th International Symposium on District Heating and Cooling.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- District heating pipes are known to degenerate with time and in some cities the pipes have been used for several decades. Due to bad insulation or cracks, energy or media leakages might appear. This paper presents a complete system for large-scale monitoring of district heating networks, including methods for detection, classification and temporal characterization of (potential) leakages. The system analyses thermal infrared images acquired by an aircraft-mounted camera, detecting the areas for which the pixel intensity is higher than normal. Unfortunately, the system also finds many false detections, i.e., warm areas that are not caused by media or energy leakages. Thus, in order to reduce the number of false detections we describe a machine learning method to classify the detections. The results, based on data from three district heating networks show that we can remove more than half of the false detections. Moreover, we also propose a method to characterize leakages over time, that is, repeating the image acquisition one or a few years later and indicate areas that suffer from an increased energy loss.
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| 8. |
- Berg, Amanda, 1988-, et al.
(författare)
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Classification of leakage detections acquired by airborne thermography of district heating networks
- 2014
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Ingår i: 2014 8th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS). - : IEEE. - 9781479972760 ; , s. 1-4
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Konferensbidrag (refereegranskat)abstract
- We address the problem of reducing the number offalse alarms among automatically detected leakages in districtheating networks. The leakages are detected in images capturedby an airborne thermal camera, and each detection correspondsto an image region with abnormally high temperature. Thisapproach yields a significant number of false positives, and wepropose to reduce this number in two steps. First, we use abuilding segmentation scheme in order to remove detectionson buildings. Second, we extract features from the detectionsand use a Random forest classifier on the remaining detections.We provide extensive experimental analysis on real-world data,showing that this post-processing step significantly improves theusefulness of the system.
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| 9. |
- Berg, Amanda, 1988-, et al.
(författare)
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Classifying district heating network leakages in aerial thermal imagery
- 2014
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we address the problem of automatically detecting leakages in underground pipes of district heating networks from images captured by an airborne thermal camera. The basic idea is to classify each relevant image region as a leakage if its temperature exceeds a threshold. This simple approach yields a significant number of false positives. We propose to address this issue by machine learning techniques and provide extensive experimental analysis on real-world data. The results show that this postprocessing step significantly improves the usefulness of the system.
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| 10. |
- Berg, Amanda, 1988-, et al.
(författare)
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Detecting Rails and Obstacles Using a Train-Mounted Thermal Camera
- 2015
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Ingår i: Image Analysis. - Cham : Springer. - 9783319196640 - 9783319196657 ; , s. 492-503
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Konferensbidrag (refereegranskat)abstract
- We propose a method for detecting obstacles on the railway in front of a moving train using a monocular thermal camera. The problem is motivated by the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. The proposed method includes a novel way of detecting the rails in the imagery, as well as a way to detect anomalies on the railway. While the problem at a first glance looks similar to road and lane detection, which in the past has been a popular research topic, a closer look reveals that the problem at hand is previously unaddressed. As a consequence, relevant datasets are missing as well, and thus our contribution is two-fold: We propose an approach to the novel problem of obstacle detection on railways and we describe the acquisition of a novel data set.
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