A closer look at context: From coxels to the contextual emergence of object saliency

Rotem Mairon, Ohad Ben-Shahar

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

Visual context is used in different forms for saliency computation. While its use in saliency models for fixations prediction is often reasoned, this is less so the case for approaches that aim to compute saliency at the object level. We argue that the types of context employed by these methods lack clear justification and may in fact interfere with the purpose of capturing the saliency of whole visual objects. In this paper we discuss the constraints that different types of context impose and suggest a new interpretation of visual context that allows the emergence of saliency for more complex, abstract, or multiple visual objects. Despite shying away from an explicit attempt to capture "objectness" (e.g., via segmentation), our results are qualitatively superior and quantitatively better than the state-of-the-art.

Original languageEnglish
Pages (from-to)708-724
Number of pages17
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8693 LNCS
Issue numberPART 5
DOIs
StatePublished - 1 Jan 2014
Event13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland
Duration: 6 Sep 201412 Sep 2014

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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