TY - JOUR
T1 - The influence of label design on search performance and noticeability in wide field of view augmented reality displays
AU - Kruijff, Ernst
AU - Orlosky, Jason
AU - Kishishita, Naohiro
AU - Trepkowski, Christina
AU - Kiyokawa, Kiyoshi
N1 - Funding Information:
This work was partially funded through the Deutsche For-schungsgemeinschaft (DFG, grants Kr 4531/1-1 and 4531/ 2-1), partially by the United States Department of the Navy, Office of Naval Research Grant #N62909-18-1-2036, and the JSPS Grant-in-aid for Scientific Research #15H02738. We also would like to thank all the participants for their time and effort while participating in the experiments. Finally, we kindly thank Katharina Stollenwerk for producing the optical flow density figures in MATLAB.
Publisher Copyright:
© 2018 IEEE.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - In Augmented Reality (AR), search performance for outdoor tasks is an important metric for evaluating the success of a large number of AR applications. Users must be able to find content quickly, labels and indicators must not be invasive but still clearly noticeable, and the user interface should maximize search performance in a variety of conditions. To address these issues, we have set up a series of experiments to test the influence of virtual characteristics such as color, size, and leader lines on the performance of search tasks and noticeability in both real and simulated environments. We evaluate two primary areas, including 1) the effects of peripheral field of view (FOV) limitations and labeling techniques on target acquisition during outdoor mobile search, and 2) the influence of local characteristics such as color, size, and motion on text labels over dynamic backgrounds. The first experiment showed that limited FOV will severely limit search performance, but that appropriate placement of labels and leaders within the periphery can alleviate this problem without interfering with walking or decreasing user comfort. In the second experiment, we found that different types of motion are more noticeable in optical versus video see-through displays, but that blue coloration is most noticeable in both. Results can aid in designing more effective view management techniques, especially for wider field of view displays.
AB - In Augmented Reality (AR), search performance for outdoor tasks is an important metric for evaluating the success of a large number of AR applications. Users must be able to find content quickly, labels and indicators must not be invasive but still clearly noticeable, and the user interface should maximize search performance in a variety of conditions. To address these issues, we have set up a series of experiments to test the influence of virtual characteristics such as color, size, and leader lines on the performance of search tasks and noticeability in both real and simulated environments. We evaluate two primary areas, including 1) the effects of peripheral field of view (FOV) limitations and labeling techniques on target acquisition during outdoor mobile search, and 2) the influence of local characteristics such as color, size, and motion on text labels over dynamic backgrounds. The first experiment showed that limited FOV will severely limit search performance, but that appropriate placement of labels and leaders within the periphery can alleviate this problem without interfering with walking or decreasing user comfort. In the second experiment, we found that different types of motion are more noticeable in optical versus video see-through displays, but that blue coloration is most noticeable in both. Results can aid in designing more effective view management techniques, especially for wider field of view displays.
KW - Augmented reality
KW - head mounted display
KW - perception
KW - peripheral vision
KW - visualization
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U2 - 10.1109/TVCG.2018.2854737
DO - 10.1109/TVCG.2018.2854737
M3 - Article
C2 - 30004877
AN - SCOPUS:85049788554
SN - 1077-2626
VL - 25
SP - 2821
EP - 2837
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
IS - 9
M1 - 8409318
ER -