Point- and Volume-Based Multi-object Acquisition in VR
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Point- and Volume-Based Multi-object Acquisition in VR. / Wu, Zhiqing; Yu, Difeng; Goncalves, Jorge.
Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings. ed. / José Abdelnour Nocera; Marta Kristín Lárusdóttir; Helen Petrie; Antonio Piccinno; Marco Winckler. Springer, 2023. p. 20-42 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14142 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Point- and Volume-Based Multi-object Acquisition in VR
AU - Wu, Zhiqing
AU - Yu, Difeng
AU - Goncalves, Jorge
N1 - Publisher Copyright: © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - Multi-object acquisition is indispensable for many VR applications. Commonly, users select a group of objects of interest to perform further transformation or analysis. In this paper, we present three multi-object selection techniques that were derived based on a two-dimensional design space. The primary design dimension concerns whether a technique acquires targets through point-based methods (selecting one object at a time) or volume-based methods (selecting a set of objects within a selection volume). The secondary design dimension examines the mechanisms of selection and deselection (cancel the selection of unwanted objects). We compared these techniques through a user study, emphasizing on scenarios with more randomly distributed objects. We discovered, for example, that the point-based technique was more efficient and robust than the volume-based techniques in environments where the targets did not follow a specific layout. We also found that users applied the deselection mechanism mostly for error correction. We provide an in-depth discussion of our findings and further distill design implications for future applications that leverage multi-object acquisition techniques in VR.
AB - Multi-object acquisition is indispensable for many VR applications. Commonly, users select a group of objects of interest to perform further transformation or analysis. In this paper, we present three multi-object selection techniques that were derived based on a two-dimensional design space. The primary design dimension concerns whether a technique acquires targets through point-based methods (selecting one object at a time) or volume-based methods (selecting a set of objects within a selection volume). The secondary design dimension examines the mechanisms of selection and deselection (cancel the selection of unwanted objects). We compared these techniques through a user study, emphasizing on scenarios with more randomly distributed objects. We discovered, for example, that the point-based technique was more efficient and robust than the volume-based techniques in environments where the targets did not follow a specific layout. We also found that users applied the deselection mechanism mostly for error correction. We provide an in-depth discussion of our findings and further distill design implications for future applications that leverage multi-object acquisition techniques in VR.
KW - Multiple targets
KW - Object selection
KW - Virtual Reality
U2 - 10.1007/978-3-031-42280-5_2
DO - 10.1007/978-3-031-42280-5_2
M3 - Article in proceedings
AN - SCOPUS:85171456577
SN - 9783031422799
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 20
EP - 42
BT - Human-Computer Interaction – INTERACT 2023 - 19th IFIP TC13 International Conference, Proceedings
A2 - Abdelnour Nocera, José
A2 - Kristín Lárusdóttir, Marta
A2 - Petrie, Helen
A2 - Piccinno, Antonio
A2 - Winckler, Marco
PB - Springer
T2 - 19th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2023
Y2 - 28 August 2023 through 1 September 2023
ER -
ID: 390399228