arrow
返回

Motion Perception: From Detection to Interpretation

delete2018-09-15
delete32
PRE
AI
S
Shin’ya Nishida *
T
Takahiro Kawabe
M
Masataka Sawayama
T
Taiki Fukiage
DOI:10.1146/annurev-vision-091517-034328delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Visual motion processing can be conceptually divided into two levels. In the lower level, local motion signals are detected by spatiotemporal-frequencys-elective sensors and then integrated into a motion vector flow. Although the model based on V1-MT physiology provides a good computational framework for this level of processing, it needs to be updated to fully explain psychophysical findings about motion perception, including complex motion signal interactions in the spatiotemporal-frequency and space domains. In the higher level, the velocity map is interpreted. Although there are many motion interpretation processes, we highlight the recent progress in research on the perception of material (e.g., specular reflection, liquid viscosity) and on animacy perception. We then consider possible linking mechanisms of the two levels and propose intrinsic flow decomposition as the key problem. To provide insights into computational mechanisms of motion perception, in addition to psychophysics and neurosciences, we review machine vision studies seeking to solve similar problems.
Keyword:
first-order motion
vector field
spatiotemporal frequency
material
animacy
intrinsic flow decomposition
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

A
Annual Review of Vision Science
IF:
5.5
论文数:
0
被引数:
1

机构

暂无机构信息
引用论文

引用论文

Home-Based Palliative Care Organizations Struggle to Survive and Thrive in a Competitive Market
err2022-03-02
err0
PREAI
errAnna Rahman; Alexis Coulourides Kogan; Nicole Lewis; Sindy Lomeli; Susan Enguidanos
err分享
err收藏
The phenomenon of walking: diverse and dynamic
err2017-12-01
err0
errOAAI
errStine Rybråten; Margrete Skår; Helena Nordh
err分享
err收藏
A Computational Approach for Obstruction-Free Photography
err2015-07-27
err173
errOAAI
errXue, Tianfan; Rubinstein, Michael; Liu, Ce; Freeman, William T.
err分享
err收藏
err分享
err收藏
学者 查看更多内容