| Title |
Perception of time to contact of slow- and fast-moving objects using monocular and binocular motion information
|
|---|---|
| Published in |
Attention, Perception, & Psychophysics, April 2018
|
| DOI | 10.3758/s13414-018-1517-8 |
| Pubmed ID | |
| Authors |
Aaron J. Fath, Mats Lind, Geoffrey P. Bingham |
| Abstract |
The role of the monocular-flow-based optical variable τ in the perception of the time to contact of approaching objects has been well-studied. There are additional contributions from binocular sources of information, such as changes in disparity over time (CDOT), but these are less understood. We conducted an experiment to determine whether an object's velocity affects which source is most effective for perceiving time to contact. We presented participants with stimuli that simulated two approaching squares. During approach the squares disappeared, and participants indicated which square would have contacted them first. Approach was specified by (a) only disparity-based information, (b) only monocular flow, or (c) all sources of information in normal viewing conditions. As expected, participants were more accurate at judging fast objects when only monocular flow was available than when only CDOT was. In contrast, participants were more accurate judging slow objects with only CDOT than with only monocular flow. For both ranges of velocity, the condition with both information sources yielded performance equivalent to the better of the single-source conditions. These results show that different sources of motion information are used to perceive time to contact and play different roles in allowing for stable perception across a variety of conditions. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 18% |
| Student > Master | 3 | 18% |
| Professor | 2 | 12% |
| Lecturer | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 5 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 6 | 35% |
| Engineering | 3 | 18% |
| Neuroscience | 2 | 12% |
| Nursing and Health Professions | 1 | 6% |
| Sports and Recreations | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 4 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 July 2018.
All research outputs
#16,287,458
of 24,003,070 outputs
Outputs from Attention, Perception, & Psychophysics
#848
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Outputs of similar age
#211,562
of 330,434 outputs
Outputs of similar age from Attention, Perception, & Psychophysics
#15
of 23 outputs
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