TY  - JOUR
A1  - Pfitzner, Christian
A1  - May, Stefan
A1  - Nüchter, Andreas
T1  - Body weight estimation for dose-finding and health monitoring of lying, standing and walking patients based on RGB-D data
JF  - Sensors
N2  - 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.
KW  - RGB-D
KW  - human body weight
KW  - image processing
KW  - kinect
KW  - machine learning
KW  - perception
KW  - segmentation
KW  - sensor fusion
KW  - stroke
KW  - thermal camera
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-176642
VL  - 18
IS  - 5
ER  - 
TY  - JOUR
A1  - Zimmerer, Chris
A1  - Fischbach, Martin
A1  - Latoschik, Marc Erich
T1  - Semantic Fusion for Natural Multimodal Interfaces using Concurrent Augmented Transition Networks
JF  - Multimodal Technologies and Interaction
N2  - 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.
KW  - multimodal fusion
KW  - multimodal interface
KW  - semantic fusion
KW  - procedural fusion methods
KW  - natural interfaces
KW  - human-computer interaction
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-197573
SN  - 2414-4088
VL  - 2
IS  - 4
ER  -