| 1. |
- Ahlberg, Jörgen, 1971-, et al.
(författare)
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Three-dimensional hyperspectral imaging technique
- 2017
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Ingår i: ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XXIII. - : SPIE - International Society for Optical Engineering. - 9781510608979 - 9781510608986
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Konferensbidrag (refereegranskat)abstract
- Hyperspectral remote sensing based on unmanned airborne vehicles is a field increasing in importance. The combined functionality of simultaneous hyperspectral and geometric modeling is less developed. A configuration has been developed that enables the reconstruction of the hyperspectral three-dimensional (3D) environment. The hyperspectral camera is based on a linear variable filter and a high frame rate, high resolution camera enabling point-to-point matching and 3D reconstruction. This allows the information to be combined into a single and complete 3D hyperspectral model. In this paper, we describe the camera and illustrate capabilities and difficulties through real-world experiments.
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| 2. |
- Andersson, Maria, et al.
(författare)
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Estimation of crowd behaviour using sensor networks and sensor fusion
- 2009
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Konferensbidrag (refereegranskat)abstract
- Commonly, surveillance operators are today monitoring a large number of CCTV screens, trying to solve the complex cognitive tasks of analyzing crowd behavior and detecting threats and other abnormal behavior. Information overload is a rule rather than an exception. Moreover, CCTV footage lacks important indicators revealing certain threats, and can also in other respects be complemented by data from other sensors. This article presents an approach to automatically interpret sensor data and estimate behaviors of groups of people in order to provide the operator with relevant warnings. We use data from distributed heterogeneous sensors (visual cameras and a thermal infrared camera), and process the sensor data using detection algorithms. The extracted features are fed into a hidden Markov model in order to model normal behavior and detect deviations. We also discuss the use of radars for weapon detection.
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| 3. |
- Andersson, Maria, et al.
(författare)
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Fusion of Acoustic and Optical Sensor Data for Automatic Fight Detection in Urban Environments
- 2010
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Ingår i: Information Fusion (FUSION), 2010 13th Conference on. - : IEEE conference proceedings. - 9780982443811 ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- We propose a two-stage method for detection of abnormal behaviours, such as aggression and fights in urban environment, which is applicable to operator support in surveillance applications. The proposed method is based on fusion of evidence from audio and optical sensors. In the first stage, a number of modalityspecific detectors perform recognition of low-level events. Their outputs act as input to the second stage, which performs fusion and disambiguation of the firststage detections. Experimental evaluation on scenes from the outdoor part of the PROMETHEUS database demonstrated the practical viability of the proposed approach. We report a fight detection rate of 81% when both audio and optical information are used. Reduced performance is observed when evidence from audio data is excluded from the fusion process. Finally, in the case when only evidence from one camera is used for detecting the fights, the recognition performance is poor.
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| 4. |
- Björklund, Svante, 1968-, et al.
(författare)
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Micro-doppler classification with boosting in perimeter protection
- 2017
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Ingår i: IET Conference Publications. - : Institution of Engineering and Technology.
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Konferensbidrag (refereegranskat)abstract
- In security surveillance at the perimeter of critical infrastructure, such as airports and power plants, approaching objects have to be detected and classified. Especially important is to distinguish between humans, animals and vehicles. In this paper, micro-Doppler data (from movement of internal parts of the target) have been collected with a small radar. From time-velocity diagrams of the data, physical features have been extracted and used in a Boosting classifier to distinguish between the classes "human", "animal" and "man-made object". This type of classifier has received much attention lately, but not in radar micro-Doppler classification. The classification result on the current data reaches 90% correct classification with this classifier. The ability to distinguish between humans and animals is good on this data. This classifier type gives insight into the classifier and the utilized features, and is easy to use. A comparison with a SVM (Support Vector Machine) classifier, which is common for micro-Doppler, has also been performed. © 2017 Institution of Engineering and Technology. All rights reserved.
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| 5. |
- Borga, Magnus, et al.
(författare)
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Signal and Anatomical Constraints in Adaptive Filtering of fMRI Data
- 2007
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Ingår i: Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. - : IEEE. - 1424406722 ; , s. 432-435
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Konferensbidrag (refereegranskat)abstract
- An adaptive filtering method for fMRI data is presented. The method is related to bilateral filtering, but with a range filter that takes into account local similarities in signal as well as in anatomy. Performance is demonstrated on simulated and real data. It is shown that using both these similarity constraints give better performance than if only one of them is used, and clearly better than standard low-pass filtering.
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| 6. |
- Dahlqvist Leinhard, Olof, et al.
(författare)
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Quantification of abdominal fat accumulation during hyperalimentation using MRI
- 2009
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Ingår i: Proceedings of the ISMRM Annual Meeting (ISMRM'09), 2009. - Berkeley, CA, USA : International Society for Magnetic Resonance in Medicine. ; , s. 206-
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- There is an increasing demand for imaging methods that can be used for automatic, accurate and quantitative determination of the amounts of abdominal fat. Such methods are important as they will allow the evaluation of some of the risk factors underlying the ’metabolic syndrome’. The metabolic syndrome is becoming common in large parts of the world, and it appears that a dominant risk factor for developing this syndrome is abdominal obesity. Subjects that are afflicted with the metabolic syndrome are exposed to a high risk for developing a large range of diseases such as type 2 diabetes, cardiac failure, and stroke. The aim of this work
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| 7. |
- Eklund, Anders, et al.
(författare)
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Balancing an Inverted Pendulum by Thinking A Real-Time fMRI Approach
- 2009
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a method for controlling a dynamical system using real-time fMRI. The objective for the subject in the MR scanner is to balance an inverse pendulum by activating the left or right hand or resting. The brain activity is classified each second by a neural network and the classification is sent to a pendulum simulator to change the force applied to the pendulum. The state of the inverse pendulum is shown to the subject in a pair of VR goggles. The subject was able to balance the inverse pendulum both with real activity and imagined activity. The developments here have a potential to aid people with communication disabilities e.g., locked in people. It might also be a tool for stroke patients to be ableto train the damaged brain area and get real-time feedback of when they do it right.
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| 8. |
- Eklund, Anders, et al.
(författare)
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Using Real-Time fMRI to Control a Dynamical System
- 2009
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Ingår i: ISMRM 17th Scientific Meeting & Exhibition. - Linköping : Linköping University Electronic Press.
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Konferensbidrag (refereegranskat)abstract
- We present e method for controlling a dynamical system using real-time fMRI. The objective for the subject in the MR scanner is to balance an inverse pendulum by activating the left or right hand or resting. The brain activity is clasified each second by a neural network and the classification is sent to a pendulum simulator to change the state of the pendulum. The state of the inverse pendulum is shown to the subject in a pair of VR goggles. The subject was able to balance the inverse pendulum during a 7 minute test run.
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| 9. |
- Eklund, Anders, et al.
(författare)
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Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We present a method for controlling a dynamical system using real-time fMRI. The objective for the subject in the MR scanner is to balance an inverted pendulum by activating the left or right hand or resting. The brain activity is classified each second by a neural network and the classification is sent to a pendulum simulator to change the force applied to the pendulum. The state of the inverted pendulum is shown to the subject in a pair of VR goggles. The subject was able to balance the inverted pendulum during several minutes, both with real activity and imagined activity. In each classification 9000 brain voxels were used and the response time for the system to detect a change of activity was on average 2-4 seconds. The developments here have a potential to aid people with communication disabilities, such as locked in people. Another future potential application can be to serve as a tool for stroke and Parkinson patients to be able to train the damaged brain area and get real-time feedback for more efficient training.
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| 10. |
- Eklund, Anders, 1981-, et al.
(författare)
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Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification
- 2009. - 1
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Ingår i: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642042676 - 9783642042683 ; , s. 1000-1008
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Konferensbidrag (refereegranskat)abstract
- We present a method for controlling a dynamical system using real-time fMRI. The objective for the subject in the MR scanner is to balance an inverted pendulum by activating the left or right hand or resting. The brain activity is classified each second by a neural network and the classification is sent to a pendulum simulator to change the force applied to the pendulum. The state of the inverted pendulum is shown to the subject in a pair of VR goggles. The subject was able to balance the inverted pendulum during several minutes, both with real activity and imagined activity. In each classification 9000 brain voxels were used and the response time for the system to detect a change of activity was on average 2-4 seconds. The developments here have a potential to aid people with communication disabilities, such as locked in people. Another future potential application can be to serve as a tool for stroke and Parkinson patients to be able to train the damaged brain area and get real-time feedback for more efficient training.
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