Comparing rapid scene categorization of aerial and terrestrial views: A new perspective on scene gist.

نویسندگان

  • Lester C Loschky
  • Ryan V Ringer
  • Katrina Ellis
  • Bruce C Hansen
چکیده

Scene gist, a viewer's holistic representation of a scene from a single eye fixation, has been extensively studied for terrestrial views, but not for aerial views. We compared rapid scene categorization of both views in three experiments to determine the degree to which diagnostic information is view dependent versus view independent.We found large differences in observers' ability to rapidly categorize aerial and terrestrial scene views, consistent with the idea that scene gist recognition is viewpoint dependent.In addition, computational modeling showed that training models on one view (aerial or terrestrial) led to poor performance on the other view, thereby providing further evidence of viewpoint dependence as a function of available information. Importantly, we found that rapid categorization of terrestrial views (but not aerial views) was strongly interfered with by image rotation, further suggesting that terrestrial-view scene gist recognition is viewpoint dependent, with aerial-view scene recognition being viewpoint independent. Furthermore, rotation-invariant texture images synthesized from aerial views of scenes were twice as recognizable as those synthesized from terrestrial views of scenes (which were at chance), providing further evidence that diagnostic information for rapid scene categorization of aerial views is viewpoint invariant. We discuss the results within a perceptual-expertise framework that distinguishes between configural and featural processing, where terrestrial views are more effectively processed due to their predictable view-dependent configurations whereas aerial views are processed less effectively due to reliance on view-independent features.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

How Does the Brain Represent Visual Scenes? A Neuromagnetic Scene Categorization Study

How are visual scenes represented in the brain during categorization? We acquired magnetoencephalography (MEG) data from nine healthy subjects who participated in a rapid natural scene categorization task. Scenes were presented in two different perspectives (aerial vs. terrestrial) and two different orientations (upright vs. inverted). We applied multivariate pattern classification to categoriz...

متن کامل

Scene gist categorization by pigeons.

Scene gist categorization in humans is rapid, accurate, and tuned to the statistical regularities in the visual world. However, no studies have investigated whether scene gist categorization is a general process shared across species, or whether it may be influenced by species-specific adaptive specializations relying on specific low-level scene statistical regularities of the environment. Alth...

متن کامل

A Global Framework for Scene Gist A Global Framework for Scene Gist

Human observers are able to rapidly and accurately categorize natural scenes, but the representation mediating this feat is still unknown. Here we propose a framework of rapid scene categorization that does not segment a scene into objects and instead uses a vocabulary of global, ecological properties that describe spatial and functional aspects of scene space (such as navigability or mean dept...

متن کامل

Processing scene context: Fast categorization and object interference

The extent to which object identification is influenced by the background of the scene is still controversial. On the one hand, the global context of a scene might be considered as an ultimate representation, suggesting that object processing is performed almost systematically before scene context analysis. Alternatively, the gist of a scene could be extracted sufficiently early to be able to i...

متن کامل

When is scene recognition just texture recognition?

Subjects were asked to discriminate scenes after very brief exposures (37-69 ms). Their performance was always above chance and increased with exposure duration, confirming that subjects can get the gist of a scene with one fixation. We propose that a simple texture analysis of the image can provide a useful cue towards rapid scene identification. Our model learns texture features across scene ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Journal of vision

دوره 15 6  شماره 

صفحات  -

تاریخ انتشار 2015