Enhancement of Direct Augmented Reality Object Selection by Gravity-Adapted Target Resizing

Abstract

Direct object selection in an Augmented Reality environment that is coded outside of human body frame of reference is deteriorated under short-term altered gravity. As countermeasures we developed a gravity-adapted resizing technique based on the Hooke’s law that resulted in two techniques of target and interface deformation (compression, elongation). To prove the concept of this resizing approach we initially conducted two experiments under simulated hypergravity conditions. While during the first study hypergravity was induced by a long-arm human centrifuge, in the second study hypergravity was simulated by additional arm weightings that were balanced and attached to the participants’ pointing arm. We investigated the difference of the task performance with respect to the pointing frequency, response time, pointing speed and accuracy, when participants performed a visuomotor task under the resizing conditions compared to the unchanged condition. During the second study we additionally evaluated the speed-accuracy tradeoff of the resizing techniques according to Fitts’ law and the physiological workload by cardiac responses analyzing the heart rate variability. Both experiments showed that the online adaption of the present gravity load to targets’ size and distance influences the performance of direct AR direct pointing. The results revealed that the pointing performance benefits from elongation target deformation by increased target sizes and distances, while pointing towards compressed targets mostly decreases the physiological workload under increased gravity conditions.

Publication
Computer Vision, Imaging and Computer Graphics Theory and Applications

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