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Understanding scene understanding

Authors: Gregory J. Zelinsky;

Understanding scene understanding

Abstract

WHAT DOES IT MEAN TO “UNDERSTAND” A SCENE? Look very briefly at the picture on the next page (Figure 1); what do you see? Decades of research has shown that it is possible to extract the gist of a scene very quickly (Potter, 1975; Friedman, 1979); even from the briefest of glances you could probably classify this scene as some sort of race. Other research has shown that some categories of objects, people and animals in particular, can also be detected from very brief exposures (Thorpe et al., 1996; Joubert et al., 2007). It may even be possible to infer from the features of a scene some properties of these objects, such as a person’s gender and perhaps their emotion (Schyns and Oliva, 1999). Actions can also be characterized by relatively simple features (see Kozlowski and Cutting, 1977 and Wang et al., 2009, for two very different approaches), with the pose adopted by someone running being especially distinctive. So in addition to detecting that there were people in this scene, you could probably also discern that these people were women and that they were running. Combining these pieces of information might therefore have led you to a simple “gist” level of interpretation—a women’s track meet. But scene understanding doesn’t stop at gist, and there were other things happening in this scene. Closer scrutiny reveals that one of the runners had fallen and that the others were trying to avoid tripping over her. These details may have gone undetected from a brief exposure for a variety of reasons. When a person falls their pose becomes highly variable, and certainly deviates from poses that we have associated with typical human activities. Moreover, this particular fall resulted in the loss of this person’s face from view. These factors would make it harder to recognize this pattern of pixels as a person, which would obviously affect whether these details would be included in a scene interpretation following a brief exposure. “Avoidance” is also a far more difficult action to detect than running, characterized by a relatively subtle shift in body posture and a slightly exaggerating leaping stride by the runner. Had these fallen and avoidance events been detected they would almost certainly have been included in the scene interpretation, but the point is that it is unsurprising that they were not. And finally, if you had noticed that all of the runners had one prosthetic leg, this critical information would be expected to fundamentally change your understanding of this scene—suddenly it tells a story about a special race for women amputees. This example illustrates the fact that scene understanding exists on a continuum. At one end is a very fast and seemingly effortless extraction of the scene’s gist—often just its category name. At the other end is the slower and often effortful attachment of deeper meaning to the scene. Although these different interpretations likely engage different underlying processes and might therefore be given different names, for the purpose of this paper I will adopt the lay person’s definition of scene understanding—what is the scene about? What is the story that it is trying to tell?

Keywords

eye movements, gist perception, Eye Movements, Psychology, scene perception, object detection, scene understanding, activity recognition, event detection, BF1-990

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    20
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Average
Green
gold