English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Rapid animal detection in natural scenes: Critical features are local

Wichmann, F., Rosas, P., & Gegenfurtner, K. (2005). Rapid animal detection in natural scenes: Critical features are local. Poster presented at Fifth Annual Meeting of the Vision Sciences Society (VSS 2005), Sarasota, FL, USA.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D479-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-3CA7-C
Genre: Poster

Files

show Files

Locators

show
hide
Description:
-

Creators

show
hide
 Creators:
Wichmann, FA1, 2, Author              
Rosas, P1, 2, Author              
Gegenfurtner, K, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: Thorpe et al (Nature 381, 1996) first showed how rapidly human observers are able to classify natural images as to whether they contain an animal or not. Whilst the basic result has been replicated using different response paradigms (yes-no versus forced-choice), modalities (eye movements versus button presses) as well as while measuring neurophysiological correlates (ERPs), it is still unclear which image features support this rapid categorisation. Recently Torralba and Oliva (Network: Computation in Neural Systems, 14, 2003) suggested that simple global image statistics can be used to predict seemingly complex decisions about the absence and/or presence of objects in natural scences. They show that the information contained in a small number (N=16) of spectral principal components (SPC)—principal component analysis (PCA) applied to the normalised power spectra of the images—is sufficient to achieve approximately 80 correct animal detection in natural scenes. Our goal was to test whether human observers make use of the power spectrum when rapidly classifying natural scenes. We measured our subjects' ability to detect animals in natural scenes as a function of presentation time (13 to 167 msec); images were immediately followed by a noise mask. In one condition we used the original images, in the other images whose power spectra were equalised (each power spectrum was set to the mean power spectrum over our ensemble of 1476 images). Thresholds for 75 correct animal detection were in the region of 20–30 msec for all observers, independent of the power spectrum of the images: this result makes it very unlikely that human observers make use of the global power spectrum. Taken together with the results of Gegenfurtner, Braun Wichmann (Journal of Vision [abstract], 2003), showing the robustness of animal detection to global phase noise, we conclude that humans use local features, like edges and contours, in rapid animal detection.

Details

show
hide
Language(s):
 Dates: 2005-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1167/5.8.376
BibTex Citekey: 3555
 Degree: -

Event

show
hide
Title: Fifth Annual Meeting of the Vision Sciences Society (VSS 2005)
Place of Event: Sarasota, FL, USA
Start-/End Date: 2005-05-06 - 2005-05-11

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Vision
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Charlottesville, VA : Scholar One, Inc.
Pages: - Volume / Issue: 5 (8) Sequence Number: - Start / End Page: 376 Identifier: ISSN: 1534-7362
CoNE: https://pure.mpg.de/cone/journals/resource/111061245811050