Thomas Larsson

A dynamic bounding volume hierarchy for generalized collision detection

In this paper, we propose a new dynamic and efficient bounding volume hierarchy for breakable objects undergoing structured and/or unstructured motion. Our object-space method is based on different ways to incrementally update the hierarchy during simulation by exploiting temporal coherence and lazy evaluation techniques. This leads to significant advantages in terms of execution speed. Furthermore, we also show how our method lends itself naturally for an adaptive low memory cost implementation, which may be of critical importance in some applications. Finally, we propose two different techniques for detecting self-intersections, one using our hierarchical data structure, and the other is an improved sorting-based method.

Efficient Collision Detection for Models Deformed by Morphing

We describe a fast and accurate collision-detection algorithm specialised for models deformed by morphing. The models considered are meshes where the vertex positions are convex combinations of sets of reference meshes. This new method is based on bounding-volume trees that are extended to support efficient tree-node updates by blending associated sets of reference bounding volumes. With our approach, it is possible to use either axis-aligned bounding boxes, discrete-orientation polytopes, or spheres as bounding volumes. The expected performance of our algorithm is of the same order as for rigid hierarchical collision detection. In our tested scenarios, the speed-up we achieved ranged from 1.5 to 58, compared to another more general algorithm for deforming bodies. (Less)

On faster sphere-box overlap testing

We present faster overlap tests between spheres and either axis-aligned or oriented boxes. By utilizing quick rejection tests, faster execution times are observed compared to previous techniques. In addition, we present alternative vectorized overlap tests, which are compared to the sequential algorithms. Source code is available online.

Bounding Volume Hierarchies of Slab Cut Balls

We introduce a bounding volume hierarchy based on the Slab Cut Ball. This novel type of enclosing shape provides an attractive balance between tightness of fit, cost of overlap testing, and memory requirement. The hierarchy construction algorithm includes a new method for the construction of tight bounding volumes in worst case O(n) time, which means our tree data structure is constructed in O(n log   n) time using traditional top‐down building methods. A fast overlap test method between two slab cut balls is also proposed, requiring as few as 28–99 arithmetic operations, including the transformation cost. Practical collision detection experiments confirm that our tree data structure is amenable for high performance collision queries. In all the tested benchmarks, our bounding volume hierarchy consistently gives performance improvements over the sphere tree, and it is also faster than the OBB tree in five out of six scenes. In particular, our method is asymptotically faster than the sphere tree, and it also outperforms the OBB tree, in close proximity situations.

The child’s perspective as a guiding principle: Young children as co-designers of an interactive application to facilitate participation in healthcare situations

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 childrens, 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 childs perspective) on the usability, content and graphic design of the application, substantially improving the software and resulting in an age-appropriate product.

The child's perspective as a guiding principle

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 childrens, 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 childs perspective) on the usability, content and graphic design of the application, substantially improving the software and resulting in an age-appropriate product.

A cascade classifier for diagnosis of melanoma in clinical images

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.

An Efficient Ellipsoid-OBB Intersection Test

An efficient algorithm to determine the intersection status between arbitrarily oriented ellipsoids and boxes (OBBs) is presented. By choosing a proper representation of the geometric objects and by utilizing an affine transformation of space, the problem is converted into a corresponding sphere-parallelepiped intersection test. Thereby, the evaluation of more costly mathematical operations other than a constant number of simple arithmetic operations and comparisons can be avoided. Further efficiency is also gained by exploiting the regularity of the involved geometric shapes, as well as early rejection tests. Practical experiments show a four-times speed-up on average when these techniques are used.

Fast and robust approximation of smallest enclosing balls in arbitrary dimensions

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.

Parallel computation of optimal enclosing balls by iterative orthant scan

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. Graphical abstractDisplay Omitted HighlightsA fast minimum enclosing ball algorithm for general dimensions.An effective heuristic drastically reducing the number of algorithmic steps.Exhaustive study of parallelization opportunities for different platforms.Real-time exact bounding sphere computation in 3D.