A quantitative theory of immediate visual recognition.
Human and non-human primates excel at visual recognition tasks. The primate visual system exhibits a strong degree of selectivity while at the same time being robust to changes in the input image. We have developed a quantitative theory to account for the computations performed by the feedforward path in the ventral stream of the primate visual cortex. Here we review recent predictions by a model instantiating the theory about physiological observations in higher visual areas. We also show that the model can perform recognition tasks on datasets of complex natural images at a level comparable to psychophysical measurements on human observers during rapid categorization tasks. In sum, the evidence suggests that the theory may provide a framework to explain the first 100-150 ms of visual object recognition. The model also constitutes a vivid example of how computational models can interact with experimental observations in order to advance our understanding of a complex phenomenon. We conclude by suggesting a number of open questions, predictions, and specific experiments for visual physiology and psychophysics.
Serre
Thomas
T
Center for Biological and Computational Learning, McGovern Institute for Brain Research, Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge 02139, USA. serre@mit.edu
Kreiman
Gabriel
G
Kouh
Minjoon
M
Cadieu
Charles
C
Knoblich
Ulf
U
Poggio
Tomaso
T
D000818:Animals; D003198:Computer Simulation; D005364:Field Dependence-Independence; D006801:Humans; D008954:Models, Biological; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation; D011601:Psychophysics; D014793:Visual Cortex / Q000502:physiology*