Neural network model for human visual perception of 3-D curvilinear motion

Xiaoming Wang; Kathleen Turano

doi:10.1117/12.138294

16 September 1992 Neural network model for human visual perception of 3-D curvilinear motion

Xiaoming Wang, Kathleen Turano

Proceedings Volume 1700, Automatic Object Recognition II; (1992) https://doi.org/10.1117/12.138294
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

This paper presents a neural network model to emulate the ability of the human visual system to detect changes in heading direction, i.e. curvilinear motion. The network consists of three layers. The input to the network is a two-dimensional velocity field, and the output is a signal representing the magnitude and the direction of the rotational component in the flow. The first layer of the network computes local differences vectors of the velocity field to define the orientation of the translational field lines. The second layer of the network extracts the instantaneous heading direction from the translational component of the velocity field. And the third layer determines the rotational component of the velocity field. The magnitude of perceived curvilinear motion is directly proportional to the magnitude of the rotational component. The simulation results match psychophysical data of four human subjects at both slow (2.0 m/s) and fast (26.4 m/s) locomotion speeds. The biological feasibility of this neural network is supported by finding in biological vision systems.

Citation Download Citation

Xiaoming Wang and Kathleen Turano "Neural network model for human visual perception of 3-D curvilinear motion", Proc. SPIE 1700, Automatic Object Recognition II, (16 September 1992); https://doi.org/10.1117/12.138294

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available