arrow
Return

Context models and out-of-context objects

delete2012-05-01
delete89
delete
OA
AI
M
Myung-Jin Choi
A
Antonio Torralba *
A
Alan S. Willsky
DOI:10.1016/j.patrec.2011.12.004delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
The context of an image encapsulates rich information about how natural scenes and objects are related to each other. Such contextual information has the potential to enable a coherent understanding of natural scenes and images. However, context models have been evaluated mostly based on the improvement of object recognition performance even though it is only one of many ways to exploit contextual information. In this paper, we present a new scene understanding problem for evaluating and applying context models. We are interested in finding scenes and objects that are out-of-context. Detecting out-of-context objects and scenes is challenging because context violations can be detected only if the relationships between objects are carefully and precisely modeled. To address this problem, we evaluate different sources of context information, and present a graphical model that combines these sources. We show that physical support relationships between objects can provide useful contextual information for both object recognition and out-of-context detection. (C) 2011 Elsevier B.V. All rights reserved.
Keywords:
Object detection
Context model
Out-of-context object
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Pattern Recognition Letters cover
Pattern Recognition Letters
IF:
3.3
Papers:
7.9K
Citations:
1.6W

Organization

No organization information available