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Cited by 292

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The Analysis of Visual Motion: From Computational Theory to Neuronal Mechanisms

Hildreth, E C, Koch, C·1987·Annual Review of Neuroscience

Abstract

The measurement and use of visual motion is one of the most fundamental abilities of biological vision systems, serving many essential functions. For example, a sudden movement in the scene might indicate an approaching predator or a desirable prey. The rapid expansion of features in the visual field can signal an object about to collide with the observer. Discontinuities in motion often occur at the locations of object boundaries and can be used to carve up the scene into distinct objects. Motion signals provide input to centers controlling eye movements, allowing objects of interest to be tracked through the scene. Relative movement can be used to infer the three-dimensional (3-D) structure and motion of object surfaces, and the movement of the observer relative to the scene, allowing biological systems to navigate quickly and efficiently through the environment. More generally, the analysis of visual motion helps us to maintain continuity of our perception of the constantly changing environment around us.

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Crossref · 10.1146/annurev.ne.10.030187.002401

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Metadata

Authors
Hildreth, E. C., & Koch, C.
Venue
Annual Review of Neuroscience
Published
1987-03
Volume
10
Issue
1
Pages
477-533
ISSN
  • 0147-006X (ISSN-L)
  • 1545-4126
OpenAlex
W2159831219
Cited by
292
References
7
FWCI
8.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Analysis of Visual Motion: From Computational Theory to Neuronal Mechanisms. https://app.cochat.ai/papers/10.1146/annurev.ne.10.030187.002401
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Hildreth, E. C., & Koch, C. (1987). The Analysis of Visual Motion: From Computational Theory to Neuronal Mechanisms. Annual Review of Neuroscience. https://doi.org/10.1146/annurev.ne.10.030187.002401

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.