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Publications (10 of 27) Show all publications
Capannini, G. & Larsson, T. B. (2018). Adaptive Collision Culling for Massive Simulations by a Parallel and Context-Aware Sweep and Prune Algorithm. IEEE Transactions on Visualization and Computer Graphics, 4(7), 2064-2077
Open this publication in new window or tab >>Adaptive Collision Culling for Massive Simulations by a Parallel and Context-Aware Sweep and Prune Algorithm
2018 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 4, no 7, p. 2064-2077Article in journal (Refereed) Published
Abstract [en]

We present an improved parallel Sweep and Prune algorithm that solves the dynamic box intersection problem in three dimensions. It scales up to very large datasets, which makes it suitable for broad phase collision detection in complex moving body simulations. Our algorithm gracefully handles high-density scenarios, including challenging clustering behavior, by using a double-axis sweeping approach and a cache-friendly succinct data structure. The algorithm is realized by three parallel stages for sorting, candidate generation, and object pairing. By the use of temporal coherence, our sorting stage runs with close to optimal load balancing. Furthermore, our approach is characterized by a work-division strategy that relies on adaptive partitioning, which leads to almost ideal scalability. In addition, for scenarios that involves intense clustering along several axes simultaneously, we propose an enhancement that increases the context-awareness of the algorithm. By exploiting information gathered along three orthogonal axes, an efficient choice of what range query to perform can be made per object during run-time. Experimental results show high performance for up to millions of objects on modern multi-core CPUs.

Keywords
Collision detection, Simulation, Parallel algorithms, Multicore processing, Multithreading, Tree data structures, Sorting
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-38938 (URN)10.1109/TVCG.2017.2709313 (DOI)000433321900001 ()2-s2.0-85047737311 (Scopus ID)
Projects
RALF3 - Software for Embedded High Performance Architectures
Available from: 2018-04-10 Created: 2018-04-10 Last updated: 2018-06-14Bibliographically approved
Stålberg, A., Sandberg, A., Larsson, T. B., Imelda, C. & Söderbäck, M. (2017). Curious, Thoughtful and Affirmative – Young Children’s Meanings of Participation in Healthcare Situations when using an Interactive Communication Tool. Journal of Clinical Nursing, 27(1-2), 235-246
Open this publication in new window or tab >>Curious, Thoughtful and Affirmative – Young Children’s Meanings of Participation in Healthcare Situations when using an Interactive Communication Tool
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2017 (English)In: Journal of Clinical Nursing, ISSN 0962-1067, E-ISSN 1365-2702, Vol. 27, no 1-2, p. 235-246Article in journal (Refereed) Published
National Category
Health Sciences
Research subject
Care Sciences
Identifiers
urn:nbn:se:mdh:diva-36447 (URN)10.1111/jocn.13878 (DOI)000418871000048 ()28514530 (PubMedID)2-s2.0-85041927697 (Scopus ID)
Available from: 2017-09-18 Created: 2017-09-18 Last updated: 2018-10-16Bibliographically approved
Källberg, L., Shellshear, E. & Larsson, T. B. (2016). An external memory algorithm for the minimum enclosing ball problem. In: VISIGRAPP 2016 - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications: . Paper presented at 11th International Conference on Computer Graphics Theory and Application, GRAPP 2016; Part of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2016, 27 February 2016 through 29 February 2016 (pp. 83-90).
Open this publication in new window or tab >>An external memory algorithm for the minimum enclosing ball problem
2016 (English)In: VISIGRAPP 2016 - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2016, p. 83-90Conference paper, Published paper (Refereed)
Abstract [en]

In this article we present an external memory algorithm for computing the exact minimum enclosing ball of a massive set of points in any dimension. We test the performance of the algorithm on real-life three-dimensional data sets and demonstrate for the first time the practical efficiency of exact out-of-core algorithms. By use of simple heuristics, we achieve near-optimal I/O in all our test cases.

Keywords
Big Data, External Memory Algorithm, Minimum Enclosing Ball, Smallest Bounding Sphere, Computation theory, Computer graphics, Computer vision, External memory algorithms, Near-optimal, Out-of-core algorithms, Simple heuristics, Test case, Three dimensional data sets, Algorithms
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-31792 (URN)2-s2.0-84968830542 (Scopus ID)9789897581755 (ISBN)
Conference
11th International Conference on Computer Graphics Theory and Application, GRAPP 2016; Part of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2016, 27 February 2016 through 29 February 2016
Available from: 2016-06-09 Created: 2016-06-09 Last updated: 2018-02-22Bibliographically approved
Larsson, T. B., Capannini, G. & Källberg, L. (2016). Parallel computation of optimal enclosing balls by iterative orthant scan. Computers & graphics, 56, 1-10
Open this publication in new window or tab >>Parallel computation of optimal enclosing balls by iterative orthant scan
2016 (English)In: Computers & graphics, ISSN 0097-8493, E-ISSN 1873-7684, Vol. 56, p. 1-10Article in journal (Refereed) Published
Abstract [en]

We propose an algorithm for computing the exact minimum enclosing ball of large point sets in general dimensions. It aims to reduce the number of passes by retrieving a well-balanced set of outliers in each linear search through the input by decomposing the space into orthants. The experimental evidence indicates that the convergence rate in terms of the required number of linear passes is superior compared to previous exact methods, and substantially faster execution times are observed in dimensions d≤16. In the important three-dimensional case, the execution times indicate real-time performance. Furthermore, we show how the algorithm can be adapted for parallel execution on both CPU and GPU architectures using OpenMP, AVX, and CUDA. For large datasets, our CUDA solution is superior. For example, the benchmark results show that optimal bounding spheres for inputs with tens of millions of points can be computed in just a few milliseconds.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-31461 (URN)10.1016/j.cag.2016.01.003 (DOI)000375813900001 ()2-s2.0-84962520463 (Scopus ID)
Available from: 2016-04-22 Created: 2016-04-22 Last updated: 2018-02-23Bibliographically approved
Stålberg, A., Sandberg, A., Söderbäck, M. & Larsson, T. B. (2016). The child’s perspective as a guiding principle: Young children as co-designers in the design of an interactive application meant to facilitate participation in healthcare situations. Journal of Biomedical Informatics, 61, 149-158
Open this publication in new window or tab >>The child’s perspective as a guiding principle: Young children as co-designers in the design of an interactive application meant to facilitate participation in healthcare situations
2016 (English)In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 61, p. 149-158Article in journal (Refereed) Published
Abstract [en]

During the last decade, interactive technology has entered mainstream society. Its many users also include children, even the youngest ones, who use the technology in different situations for both fun and learning. When designing technology for children, it is crucial to involve children in the process in order to arrive at an age-appropriate end product. In this study we describe the specific iterative process by which an interactive application was developed. This application is intended to facilitate young children's, three-to five years old, participation in healthcare situations. We also describe the specific contributions of the children, who tested the prototypes in a preschool, a primary health care clinic and an outpatient unit at a hospital, during the development process. The iterative phases enabled the children to be involved at different stages of the process and to evaluate modifications and improvements made after each prior iteration. The children contributed their own perspectives(the child's perspective) on the usability, content and graphic design of the application, substantially improving the software and resulting in an age-appropriate product.

Keywords
children's perspective, interactive computer design, health care, participation
National Category
Health Sciences
Research subject
Care Sciences
Identifiers
urn:nbn:se:mdh:diva-31397 (URN)10.1016/j.jbi.2016.03.024 (DOI)000384704300016 ()27050824 (PubMedID)2-s2.0-84962777466 (Scopus ID)
Projects
IACTA Interactive communication tool activities
Available from: 2016-04-08 Created: 2016-04-08 Last updated: 2018-02-23Bibliographically approved
Källberg, L. & Larsson, T. B. (2015). Faster Approximation of Minimum Enclosing Balls by Distance Filtering and GPU Parallelization. Journal of Graphics Tools, 17(3), 67-84
Open this publication in new window or tab >>Faster Approximation of Minimum Enclosing Balls by Distance Filtering and GPU Parallelization
2015 (English)In: Journal of Graphics Tools, ISSN 2165-3488, Vol. 17, no 3, p. 67-84Article in journal (Refereed) Published
Abstract [en]

Minimum enclosing balls are used extensively to speed up multidimensional data processing in, e.g., machine learning, spatial databases, and computer graphics. We present a case study of several acceleration techniques that are applicable in enclosing ball algorithms based on repeated farthest-point queries. Two different distance filtering heuristics are proposed aiming at reducing the cost of the farthest-point queries as much as possible by exploiting lower and upper distance bounds. Furthermore, auto-tunable GPU solutions using CUDA are developed for both low- and high-dimensional cases. Empirical tests apply these techniques to two recent algorithms and demonstrate substantial speedups of the ball computations. Our results also indicate that a combination of the approaches has the potential to give further performance improvements.

Place, publisher, year, edition, pages
United States: Taylor & Francis, 2015
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-29243 (URN)10.1080/2165347X.2015.1037471 (DOI)
Projects
RALF3 - Software for Embedded High Performance Architectures
Available from: 2015-10-06 Created: 2015-09-29 Last updated: 2018-02-23Bibliographically approved
Sabouri, P., Gholam Hosseini, H., Larsson, T. B. & Collins, J. (2014). A Cascade Classifier for Diagnosis of Melanoma in Clinical Images. In: The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC14: . Paper presented at The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC14, 26 Aug 2014, Chicago, United States (pp. 6748-6751).
Open this publication in new window or tab >>A Cascade Classifier for Diagnosis of Melanoma in Clinical Images
2014 (English)In: The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC14, 2014, p. 6748-6751Conference paper, Published paper (Refereed)
Abstract [en]

Computer aided diagnosis of medical images can help physicians in better detecting and early diagnosis of many symptoms and therefore reducing the mortality rate. Realization of an efficient mobile device for semi-automatic diagnosis of melanoma would greatly enhance the applicability of medical image classification scheme and make it useful in clinical contexts. In this paper, interactive object recognition methodology is adopted for border segmentation of clinical skin lesion images. In addition, performance of five classifiers, KNN, Naïve Bayes, multi-layer perceptron, random forest and SVM are compared based on color and texture features for discriminating melanoma from benign nevus. The results show that a sensitivity of 82.6% and specificity of 83% can be achieved using a single SVM classifier. However, a better classification performance was achieved using a proposed cascade classifier with the sensitivity of 83.06% and specificity of 90.05% when performing ten-fold cross validation.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-26781 (URN)10.1109/EMBC.2014.6945177 (DOI)2-s2.0-84929494210 (Scopus ID)978-1-4244-7929-0 (ISBN)
Conference
The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC14, 26 Aug 2014, Chicago, United States
Projects
RALF3 - Software for Embedded High Performance Architectures
Available from: 2014-12-04 Created: 2014-12-02 Last updated: 2018-02-22Bibliographically approved
Källberg, L. & Larsson, T. B. (2014). Accelerated Computation of Minimum Enclosing Balls by GPU Parallelization and Distance Filtering. In: Proceedings of SIGRAD 2014 SIGRAD 2014: . Paper presented at SIGRAD 2014 SIGRAD 2014, 12 Jun 2014, Gothenburg, Sweden.
Open this publication in new window or tab >>Accelerated Computation of Minimum Enclosing Balls by GPU Parallelization and Distance Filtering
2014 (English)In: Proceedings of SIGRAD 2014 SIGRAD 2014, 2014Conference paper, Published paper (Refereed)
Abstract [en]

Minimum enclosing balls are used extensively to speed up multidimensional data processing in, e.g., machine learning, spatial databases, and computer graphics. We present a case study of several acceleration techniques that are applicable in enclosing ball algorithms based on repeated farthest-point queries. Parallel GPU solutions using CUDA are developed for both low- and high-dimensional cases. Furthermore, two different distance filtering heuristics are proposed aiming at reducing the cost of the farthest-point queries as much as possible by exploiting lower and upper distance bounds. Empirical tests show encouraging results. Compared to a sequential CPU version of the algorithm, the GPU parallelization runs up to 11 times faster. When applying the distance filtering techniques, further speedups are observed.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-26452 (URN)
Conference
SIGRAD 2014 SIGRAD 2014, 12 Jun 2014, Gothenburg, Sweden
Projects
RALF3 - Software for Embedded High Performance Architectures
Available from: 2014-10-31 Created: 2014-10-31 Last updated: 2018-02-22Bibliographically approved
Källberg, L. & Larsson, T. B. (2014). Improved pruning of large data sets for the minimum enclosing ball problem. Graphical Models, 76(6), 609-619
Open this publication in new window or tab >>Improved pruning of large data sets for the minimum enclosing ball problem
2014 (English)In: Graphical Models, ISSN 1524-0703, E-ISSN 1524-0711, Vol. 76, no 6, p. 609-619Article in journal (Refereed) Published
Abstract [en]

Minimum enclosing ball algorithms are studied extensively as a tool in approximation and classification of multidimensional data. We present pruning techniques that can accelerate several existing algorithms by continuously removing interior points from the input. By recognizing a key property shared by these algorithms, we derive tighter bounds than have previously been presented, resulting in twice the effect on performance. Furthermore, only minor modifications are required to incorporate the pruning procedure. The presented bounds are independent of the dimension, and empirical evidence shows that the pruning procedure remains effective in dimensions up to at least 200. In some cases, performance improvements of two orders of magnitude are observed for large data sets. © 2014 Elsevier Inc. All rights reserved.

Keywords
Acceleration techniques, Bounding spheres, Culling, Minimum enclosing balls, Pruning
National Category
Computer and Information Sciences Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-25799 (URN)10.1016/j.gmod.2014.06.003 (DOI)000347018500050 ()2-s2.0-84905501009 (Scopus ID)
Available from: 2014-08-20 Created: 2014-08-20 Last updated: 2018-02-23Bibliographically approved
Larsson, T. B. & Källberg, L. (2013). Fast and robust approximation of smallest enclosing balls in arbitrary dimensions. Computer graphics forum (Print), 32(5), 93-101
Open this publication in new window or tab >>Fast and robust approximation of smallest enclosing balls in arbitrary dimensions
2013 (English)In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 32, no 5, p. 93-101Article in journal (Refereed) Published
Abstract [en]

In this paper, an algorithm is introduced that computes an arbitrarily fine approximation of the smallest enclosing ball of a point set in any dimension. This operation is important in, for example, classification, clustering, and data mining. The algorithm is very simple to implement, gives reliable results, and gracefully handles large problem instances in low and high dimensions, as confirmed by both theoretical arguments and empirical evaluation. For example, using a CPU with eight cores, it takes less than two seconds to compute a 1.001-approximation of the smallest enclosing ball of one million points uniformly distributed in a hypercube in dimension 200. Furthermore, the presented approach extends to a more general class of input objects, such as ball sets. 

Keywords
Arbitrary dimension, Empirical evaluations, General class, High dimensions, Large problems, Reliable results, Robust approximations, Theoretical arguments, Computer graphics, Approximation algorithms
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mdh:diva-21268 (URN)10.1111/cgf.12176 (DOI)000323204000010 ()2-s2.0-84882797817 (Scopus ID)
Available from: 2013-09-06 Created: 2013-09-06 Last updated: 2018-02-23Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1550-0994

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