Paper accepted at MDPI Electronics

Our paper “Controlling Teleportation-Based Locomotion in Virtual Reality with Hand Gestures: A Comparative Evaluation of Two-Handed and One-Handed Techniques” got accepted at MDPI Electronics for a Special Issue on Recent Advances in Virtual Reality and Augmented Reality.

Paper: https://www.mdpi.com/2079-9292/10/6/715 (available as Open Access)
Authors: Alexander SchäferGerd ReisDidier Stricker

Abstract: Virtual Reality (VR) technology offers users the possibility to immerse and freely navigate through virtual worlds. An important component for achieving a high degree of immersion in VR is locomotion. Often discussed in the literature, a natural and effective way of controlling locomotion is still a general problem which needs to be solved. Recently, VR headset manufacturers have been integrating more sensors, allowing hand or eye tracking without any additional required equipment. This enables a wide range of application scenarios with natural freehand interaction techniques where no additional hardware is required. This paper focuses on techniques to control teleportation-based locomotion with hand gestures, where users are able to move around in VR using their hands only. With the help of a comprehensive study involving 21 participants, four different techniques are evaluated. The effectiveness and efficiency as well as user preferences of the presented techniques are determined. Two two-handed and two one-handed techniques are evaluated, revealing that it is possible to move comfortable and effectively through virtual worlds with a single hand only.

TiCAM Dataset for in-Cabin Monitoring released

As part of the research activities of DFKI Augmented Vision in the VIZTA project (https://www.vizta-ecsel.eu/), we have published the open-source dataset for automotive in-cabin monitoring with a wide-angle time-of-flight depth sensor. The TiCAM dataset represents a variety of in-car person behavior scenarios and is annotated with 2D/3D bounding boxes, segmentation masks and person activity labels. The dataset is available here https://vizta-tof.kl.dfki.de/. The publication describing the dataset in detail is available as a preprint here: https://arxiv.org/pdf/2103.11719.pdf

Contacts: Jason Rambach, Jigyasa Katrolia