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This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients.
Given points in the plane, connect them using minimum ink. Though the task seems simple, it turns out to be very time consuming. In fact, scientists believe that computers cannot efficiently solve it. So, do we have to resign? This book examines such NP-hard network-design problems, from connectivity problems in graphs to polygonal drawing problems on the plane. First, we observe why it is so hard to optimally solve these problems. Then, we go over to attack them anyway. We develop fast algorithms that find approximate solutions that are very close to the optimal ones. Hence, connecting points with slightly more ink is not hard.
A complete simulation system is proposed that can be used as an educational tool by physicians in training basic skills of Minimally Invasive Vascular Interventions. In the first part, a surface model is developed to assemble arteries having a planar segmentation. It is based on Sweep Surfaces and can be extended to T- and Y-like bifurcations. A continuous force vector field is described, representing the interaction between the catheter and the surface. The computation time of the force field is almost unaffected when the resolution of the artery is increased.
The mechanical properties of arteries play an essential role in the study of the circulatory system dynamics, which has been becoming increasingly important in the treatment of cardiovascular diseases. In Virtual Reality Simulators, it is crucial to have a tissue model that responds in real time. In this work, the arteries are discretized by a two dimensional mesh and the nodes are connected by three kinds of linear springs. Three tissue layers (Intima, Media, Adventitia) are considered and, starting from the stretch-energy density, some of the elasticity tensor components are calculated. The physical model linearizes and homogenizes the material response, but it still contemplates the geometric nonlinearity. In general, if the arterial stretch varies by 1% or less, then the agreement between the linear and nonlinear models is trustworthy.
In the last part, the physical model of the wire proposed by Konings is improved. As a result, a simpler and more stable method is obtained to calculate the equilibrium configuration of the wire. In addition, a geometrical method is developed to perform relaxations. It is particularly useful when the wire is hindered in the physical method because of the boundary conditions. The physical and the geometrical methods are merged, resulting in efficient relaxations. Tests show that the shape of the virtual wire agrees with the experiment. The proposed algorithm allows real-time executions and the hardware to assemble the simulator has a low cost.
Semantic Fusion for Natural Multimodal Interfaces using Concurrent Augmented Transition Networks
(2018)
Semantic fusion is a central requirement of many multimodal interfaces. Procedural methods like finite-state transducers and augmented transition networks have proven to be beneficial to implement semantic fusion. They are compliant with rapid development cycles that are common for the development of user interfaces, in contrast to machine-learning approaches that require time-costly training and optimization. We identify seven fundamental requirements for the implementation of semantic fusion: Action derivation, continuous feedback, context-sensitivity, temporal relation support, access to the interaction context, as well as the support of chronologically unsorted and probabilistic input. A subsequent analysis reveals, however, that there is currently no solution for fulfilling the latter two requirements. As the main contribution of this article, we thus present the Concurrent Cursor concept to compensate these shortcomings. In addition, we showcase a reference implementation, the Concurrent Augmented Transition Network (cATN), that validates the concept’s feasibility in a series of proof of concept demonstrations as well as through a comparative benchmark. The cATN fulfills all identified requirements and fills the lack amongst previous solutions. It supports the rapid prototyping of multimodal interfaces by means of five concrete traits: Its declarative nature, the recursiveness of the underlying transition network, the network abstraction constructs of its description language, the utilized semantic queries, and an abstraction layer for lexical information. Our reference implementation was and is used in various student projects, theses, as well as master-level courses. It is openly available and showcases that non-experts can effectively implement multimodal interfaces, even for non-trivial applications in mixed and virtual reality.
Historical maps are fascinating documents and a valuable source of information for scientists of various disciplines. Many of these maps are available as scanned bitmap images, but in order to make them searchable in useful ways, a structured representation of the contained information is desirable.
This book deals with the extraction of spatial information from historical maps. This cannot be expected to be solved fully automatically (since it involves difficult semantics), but is also too tedious to be done manually at scale.
The methodology used in this book combines the strengths of both computers and humans: it describes efficient algorithms to largely automate information extraction tasks and pairs these algorithms with smart user interactions to handle what is not understood by the algorithm. The effectiveness of this approach is shown for various kinds of spatial documents from the 16th to the early 20th century.