| 1. |
- Kolbe, Viktor, et al.
(author)
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Indoor Photorealistic 3D Mapping using Stereo Images from SLR Cameras
- 2009
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In: Proceedings of the '09 Swedish Symposium on Image Analysis (SSBA). - Linköping : Linköping University Electronic Press. - 9789163339240
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Conference paper (other academic/artistic)abstract
- Creating a 3D model from photos require an estimate of the position and orientation (pose) of the camera for each photo that is acquired. This paper presents a method to estimate the camera pose using only image data. The images are acquired at a low frequency using a stereo rig, consisting of two rigidly attached SLR cameras. Features are extracted and an optimization problem is solved for each new stereo image. The results are used to merge multiple stereo images and building a larger model of the scene. The accumulated error after processing 10 images can with the present methods be less than 1.2 mm in translation and 0.1 degrees in rotation.
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| 2. |
- Chandaria, Jigna, et al.
(author)
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Real-Time Camera Tracking in the MATRIS Project
- 2006
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In: Prcoeedings of the 2006 International Broadcasting Convention.
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Conference paper (peer-reviewed)abstract
- In order to insert a virtual object into a TV image, the graphics system needs to know precisely how the camera is moving, so that the virtual object can be rendered in the correct place in every frame. Nowadays this can be achieved relatively easily in postproduction, or in a studio equipped with a special tracking system. However, for live shooting on location, or in a studio that is not specially equipped, installing such a system can be difficult or uneconomic. To overcome these limitations, the MATRIS project is developing a real-time system for measuring the movement of a camera. The system uses image analysis to track naturally occurring features in the scene, and data from an inertial sensor. No additional sensors, special markers, or camera mounts are required. This paper gives an overview of the system and presents some results.
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| 3. |
- Chandaria, Jigna, et al.
(author)
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Real-Time Camera Tracking in the MATRIS Project
- 2007
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In: Smpte Journal. - 0036-1682. ; 116:7-8, s. 266-271
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Journal article (peer-reviewed)abstract
- In order to insert a virtual object into a TV image, the graphics system needs to know precisely how the camera is moving, so that the virtual object can be rendered in the correct place in every frame. Nowadays this can be achieved relatively easily in post-production, or in a studio equipped with a special tracking system. However, for live shooting on location, or in a studio that is not specially equipped, installing such a system can be difficult or uneconomic. To overcome these limitations, the MATRIS project is developing a real-time system for measuring the movement of a camera. The system uses image analysis to track naturally occurring features in the scene, and data from an inertial sensor. No additional sensors, special markers, or camera mounts are required. This paper gives an overview of the system and presents some results.
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| 4. |
- Gerdin, Markus, 1977-, et al.
(author)
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Noise Modeling, State Estimation and System Identification in Linear Differential-Algebraic Equations
- 2004
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In: Proceedings of the 5th Conference on Computer Science and Systems Engineering. - Linköping : Linköping University Electronic Press. ; , s. 153-163
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Conference paper (other academic/artistic)abstract
- This paper treats how parameter estimation and Kalman filtering can be performed using a Modelica model. The procedures for doing this have been developed earlier by the authors, and are here exemplified on a physical system. It is concluded that the parameter and state estimation problems can be solved using the Modelica model, and that the parameters estimation and observer construction to a large extent could be automated with relatively small changes to a Modelica environment.
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| 5. |
- Gerdin, Markus, 1977-, et al.
(author)
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On Parameter and State Estimation for Linear Differential-Algebraic Equations
- 2007
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In: Automatica. - Linköping : Elsevier. - 0005-1098 .- 1873-2836. ; 43:3, s. 416-425
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Journal article (peer-reviewed)abstract
- The current demand for more complex models has initiated a shift away from state-space models towards models described by differential-algebraic equations (DAEs). These models arise as the natural product of object-oriented modeling languages, such as Modelica. However, the mathematics of DAEs is somewhat more involved than the standard state-space theory. The aim of this work is to present a well-posed description of a linear stochastic differential-algebraic equation and more importantly explain how well-posed estimation problems can be formed. We will consider both the system identification problem and the state estimation problem. Besides providing the necessary theory we will also explain how the procedures can be implemented by means of efficient numerical methods.
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| 6. |
- Gustafsson, Stefan, et al.
(author)
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Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients
- 2022
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12
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Journal article (peer-reviewed)abstract
- Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a lack of high-performing models for the diagnosis of myocardial infarction in real-world scenarios. We aimed to train and validate a deep learning model using ECGs to predict myocardial infarction in real-world emergency department patients. We studied emergency department patients in the Stockholm region between 2007 and 2016 that had an ECG obtained because of their presenting complaint. We developed a deep neural network based on convolutional layers similar to a residual network. Inputs to the model were ECG tracing, age, and sex; and outputs were the probabilities of three mutually exclusive classes: non-ST-elevation myocardial infarction (NSTEMI), ST-elevation myocardial infarction (STEMI), and control status, as registered in the SWEDEHEART and other registries. We used an ensemble of five models. Among 492,226 ECGs in 214,250 patients, 5,416 were recorded with an NSTEMI, 1,818 a STEMI, and 485,207 without a myocardial infarction. In a random test set, our model could discriminate STEMIs/NSTEMIs from controls with a C-statistic of 0.991/0.832 and had a Brier score of 0.001/0.008. The model obtained a similar performance in a temporally separated test set of the study sample, and achieved a C-statistic of 0.985 and a Brier score of 0.002 in discriminating STEMIs from controls in an external test set. We developed and validated a deep learning model with excellent performance in discriminating between control, STEMI, and NSTEMI on the presenting ECG of a real-world sample of the important population of all-comers to the emergency department. Hence, deep learning models for ECG decision support could be valuable in the emergency department.
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| 7. |
- Lindsten, Fredrik, 1984-, et al.
(author)
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An Explicit Variance Reduction Expression for the Rao-Blackwellised Particle Filter
- 2010
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Reports (other academic/artistic)abstract
- Particle filters (PFs) have shown to be very potent tools for state estimation in nonlinear and/or non-Gaussian state-space models. For certain models, containing a conditionally tractable substructure (typically conditionally linear Gaussian or with finite support), it is possible to exploit this structure in order to obtain more accurate estimates. This has become known as Rao-Blackwellised particle filtering (RBPF). However, since the RBPF is typically more computationally demanding than the standard PF per particle, it is not always beneficial to resort to Rao-Blackwellisation. For the same computational effort, a standard PF with an increased number of particles, which would also increase the accuracy, could be used instead. In this paper, we have analysed the asymptotic variance of the RBPF and provide an explicit expression for the obtained variance reduction. This expression could be used to make an efficient discrimination of when to apply Rao-Blackwellisation, and when not to.
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| 8. |
- Murray, Lawrence, et al.
(author)
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Delayed sampling and automatic Rao-Blackwellization of probabilistic programs
- 2018
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In: Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarote, Spain, April, 2018. - : PMLR.
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Conference paper (peer-reviewed)abstract
- We introduce a dynamic mechanism for the solution of analytically-tractable substructure in probabilistic programs, using conjugate priors and affine transformations to reduce variance in Monte Carlo estimators. For inference with Sequential Monte Carlo, this automatically yields improvements such as locallyoptimal proposals and Rao–Blackwellization. The mechanism maintains a directed graph alongside the running program that evolves dynamically as operations are triggered upon it. Nodes of the graph represent random variables, edges the analytically-tractable relationships between them. Random variables remain in the graph for as long as possible, to be sampled only when they are used by the program in a way that cannot be resolved analytically. In the meantime, they are conditioned on as many observations as possible. We demonstrate the mechanism with a few pedagogical examples, as well as a linearnonlinear state-space model with simulated data, and an epidemiological model with real data of a dengue outbreak in Micronesia. In all cases one or more variables are automatically marginalized out to significantly reduce variance in estimates of the marginal likelihood, in the final case facilitating a randomweight or pseudo-marginal-type importance sampler for parameter estimation. We have implemented the approach in Anglican and a new probabilistic programming language called Birch.
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| 9. |
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| 10. |
- Ancuti, Codruta O., et al.
(author)
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NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
- 2023
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In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). - Vancover : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- This study assesses the outcomes of the NTIRE 2023 Challenge on Non-Homogeneous Dehazing, wherein novel techniques were proposed and evaluated on new image dataset called HD-NH-HAZE. The HD-NH-HAZE dataset contains 50 high resolution pairs of real-life outdoor images featuring nonhomogeneous hazy images and corresponding haze-free images of the same scene. The nonhomogeneous haze was simulated using a professional setup that replicated real-world conditions of hazy scenarios. The competition had 246 participants and 17 teams that competed in the final testing phase, and the proposed solutions demonstrated the cutting-edge in image dehazing technology.
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