The Impact of Target Depth on Pointing Performance

被引:28
作者
Janzen, Izabelle [1 ]
Rajendran, Vasanth K. [2 ]
Booth, Kellogg S. [1 ]
机构
[1] Univ British Columbia, Comp Sci, Vancouver, BC V5Z 1M9, Canada
[2] Facebook, Cambridge, MA USA
来源
34TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2016 | 2016年
关键词
Binocular depth; Fitts's Law; mid-air pointing; virtual environments; Welford's model; CONTROL-DISPLAY GAIN;
D O I
10.1145/2858036.2858244
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An important visual cue for the distance to a target is its binocular depth, the disparity between the left and right eyes. We examined mid-air pointing on a large screen, varying the physical distances (depths) to targets. Welford's two-part formulation provided a better model than the one-part Fitts's Law formulation to predict movement time from movement amplitude and target width. Angular measures suggested by Kopper et al. did not improve the model. Consistent variations of Shoemaker et al.'s k-factor suggest target depth plays a role similar to gain for mid-air pointing. We compared both physical and virtual targets to determine if artificial binocular depth cues induce the same performance as purely physical binocular depth cues. Variation of the k-factor was different when virtual depth and physical depth were not identical. This has implications for calibrating 3-D virtual environments and for the design of interactive 3-D pointing techniques for those environments.
引用
收藏
页码:188 / 199
页数:12
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