TY  - JOUR
AB  - Locomotion and vison are closely linked. When users explore virtual environments by walking they rely on stable visible landmarks to plan and execute their next movement. In my research I am developing novel methods to predict locomotion paths of human subjects for the immediate future, i.e. the next few seconds. I aim to connect different types of behavioral data (eye, hand, feet and head tracking) and test their reliability and validity for predicting walking behavior in virtual reality. Such a prediction will be very valuable for natural interaction, for example in redirected walking schemes. My approach begins with an evaluation of the quality of data gathered with current tracking methods. Informative experimental conditions need to be developed to find meaningful patterns in natural walking. Next, raw tracked data of different modalities need to be connected with each other and aggregated in a useful way. Thereafter, possible valid predictors need to be developed and compared to already functioning predicting algorithms (e.g. [2, 6, 12]). As a final goal, all valid predictors shall be used to create a prediction algorithm returning the most likely future path when exploring virtual environments.
AU  - Stein, Niklas
DA  - 2021-05-06
KW  - Virtual Reality
KW  - Locomotion
KW  - Path Prediction
KW  - Eye Tracking
KW  - Latency
LA  - eng
N1  - 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2021. ISBN 978-1-6654-1166-0, pp. 727-728
N1  - Förderer: Deutsche Forschungsgemeinschaft / Projektnummer: 274361309
N1  - Funding organisation: Deutsche Forschungsgemeinschaft / Project number: 274361309
N1  - Förderer: European Commission / Projektnummer: 734227
N1  - Funding organisation: European Commission / Project number: 734227
PY  - 2021-05-06
TI  - Analyzing Visual Perception and Predicting Locomotion using Virtual Reality and Eye Tracking
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:6-35079486659
Y2  - 2024-12-26T17:41:01
ER  -