Download Feature Detection Model

The Visual System:
Feature Detection
Model
Lesson 17
Cortical Mechanisms
Primary Visual Cortex - V1
 Striate or calcarine cortex
 Hubel and Wiesel - Nobel Prize
 Single cell recording
 Feature detection model
 simple stimuli  complex perceptions ~

Feature Detection Model
Visual perception of objects
 detection of simple features
 points, lines, corners, curves
 Convergence of information
 retina  LGN V1
 Primary Visual Cortex (V1)
 Simple cells
 complex cells
 hypercomplex cells ~

Simple Cells
Detect lines & edges
 not center-surround
 Best stimulus
 bar of light or line
 particular orientation
 particular location ~

Simple Cells
LGN neurons RF
 center-surround
 converge onto simple cells (V1)
 Bar of light
  APs in simple cell ~

Simple Cells
Wrong
location
Wrong
angle
LGN
Simple
Cell

V1
wrong location or angle
 doesn’t affect simple cell ~
Complex Cells
In V1 & V2 (secondary visual cortex)
 Convergence
 of LGN & simple cells
 responds to movement
 Best stimulus
 line or bar
 Fixed angular orientation
 Location not as important
 preferred direction of movement ~

Complex Cells
V1
V1/V2
S1 S2 S3
Complex
Cell
Hypercomplex Cells
V1 & V2
 Complex cells converge
 Hypercomplex cells
 Best stimulus
 lines of specific length
 Detect Corners ~

Feature Detection Theory

Features = lines & corners
 Can it represent a curve?