Influence of Object's Movement Speed on Human Depth Perception in Three-Dimensional Space
At present, with the rapid development of artificial intelligence technology, the demand for human-computer interaction is becoming more and more complex. How to improve the realistic experience of depth perception for three-dimensional display products like virtual reality is one of the difficulties. This study aims to investigate the influence of object's movement speed on human depth perception in three-dimensional space. Based on the concept and previous studies of motion parallax cue on human depth perception, the nearer objects appear to move faster than the further ones, indicating there might be relationship between depth perception and movement speed. This study designed a group of psychophysical experiment by using random-dot specified sinusoidal stimulus and operating it moving in five speeds (0, 5, 10, 15, and 20 arcmin/s); and examined whether the object's movement speed have influence on the depth perception in three-dimensional space. Experimental results show that when the object moves at a relatively low speed, the contribution of motion parallax caused by this movement to depth perception is relatively small, even with a certain negative effect which might be due to the depth aftereffects involved. However, when at relatively high movement speed, the motion parallax has a certain improvement on depth perception, which also suggest the involvement of interaction between the binocular disparity and motion parallax. These results can also provide data support for improving the realistic experience of depth perception in human-computer interaction.
Authors
- Yuanrui Dong
- Yanfei Wang (ORCID: https://orcid.org/0000-0001-7992-3999)
- Jinyuan Liu (ORCID: https://orcid.org/0000-0003-2085-2676)
- Shufang He (ORCID: https://orcid.org/0000-0003-1265-2412)
- Caihong Dai
- Ruoduan Sun (ORCID: https://orcid.org/0009-0004-0463-602X)
- Shuai Li
Institutions
- National Institute of Metrology (CN)
Publication Details
- Published
- 2025-06-06
- DOI
- https://doi.org/10.1109/dlcv65218.2025.11088437
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- National Institute of Metrology, China