When we try to acquire a moving target such as hitting a virtual tennis in a computer game, we must hit the target instantly when it flies over our hitting range. In other words, we have to acquire the target in spatial and temporal domains simultaneously. We call this type of task spatiotemporal moving target selection, which we find is common yet less studied in HCI. This paper presents a tentative model for predicting the error rates in spatiotemporal moving target selection. Our model integrates two latest models, the Ternary-Gaussian model and the Temporal Pointing model, to explain the influence of spatial and temporal constraints on pointing errors. In a 12-subject pointing experiment with a computer mouse, our model shows high fitting results with 0.904 R2. We discuss future research directions on this topic and how it could potentially help the design in dynamical user interfaces.
|Title of host publication||CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems|
|Publisher||Association for Computing Machinery|
|Publication status||Published - 2019 May 2|
|Event||2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019 - Glasgow, United Kingdom|
Duration: 2019 May 4 → 2019 May 9
|Name||Conference on Human Factors in Computing Systems - Proceedings|
|Conference||2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019|
|Period||19/5/4 → 19/5/9|
Bibliographical noteFunding Information:
This work was supported by National Key R&D Program of China (Grant No. 2016YFB1001405), the National Natural Science Foundation of China (Grant No. 61802379) and Key Research Program of Frontier Sciences, CAS (Grant No. QYZDY-SSW-JSC041).
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All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design