Angelika Dierker

A Calibration-Free Head Gesture Recognition System with Online Capability

In this paper, we present a calibration-free head gesture recognition system using a motion-sensor-based approach. For data acquisition we conducted a comprehensive study with 10 subjects. We analyzed the resulting head movement data with regard to separability and transferability to new subjects. Ordered means models (OMMs) were used for classification, since they provide an easy-to-use, fast, and stable approach to machine learning of time series. In result, we achieved classification rates of 85-95% for nodding, head shaking and tilting head gestures and good transferability. Finally, we show first promising attempts towards online recognition.

Visual search in the (un)real world: how head-mounted displays affect eye movements, head movements and target detection

Head-mounted displays (HMDs) that use a see-through display method allow for superimposing computer-generated images upon a real-world view. Such devices, however, normally restrict the users field of view. Furthermore, low display resolution and display curvature are suspected to make foveal as well as peripheral vision more difficult and may thus affect visual processing. In order to evaluate this assumption, we compared performance and eye-movement patterns in a visual search paradigm under different viewing conditions: participants either wore an HMD, had their field of view restricted by blinders or could avail themselves of an unrestricted field of view (normal viewing). From the head and eye-movement recordings we calculated the contribution of eye rotation to lateral shifts of attention. Results show that wearing an HMD leads to less eye rotation and requires more head movements than under blinders conditions and during normal viewing.

Collaboration in Augmented Reality: How to establish coordination and joint attention?

We present an initial investigation from a semi-experimental setting, in which an HMD-based AR-system has been used for real-time collaboration in a task-oriented scenario (design of a museum exhibition). Analysis points out the specific conditions of interacting in an AR environment and focuses on one particular practical problem for the participants in coordinating their interaction: how to establish joint attention towards the same object or referent. Analysis allows insights into how the pair of users begins to familarize with the environment, the limitations and opportunities of the setting and how they establish new routines for e.g. solving the ‘joint attention’-problem.