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A New Gait-Based Identification Method Using Local Gauss Maps Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Search Guided Saliency

Authors : Shijian Lu, Byung-Uck Kim, Nicolas Lomenie, Joo-Hwee Lim, Jianfei Cai

Published in: Computer Vision - ACCV 2014 Workshops

Publisher: Springer International Publishing

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Abstract

We propose a new type of saliency as inspired by findings from visual search studies - the searching difficulty is correlated with the target-distractor contrast, the distractor homogeneity, as well as the target uniqueness. By putting an image pixel as the target and the surrounding pixels as distractors, a search guided saliency model is designed in accordance with these findings. In particular, three saliency measures in correspondence to the three searching factors are simultaneously computed and integrated by using a series of contextual histograms. The proposed model has been evaluated over three public datasets and experiments show superior prediction of the human fixations when compared to the state-of-the-art models.

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previous chapter Large-Scale Indoor/Outdoor Image Classification via Expert Decision Fusion (EDF)
next chapter Salient Object Detection via Saliency Spread
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Metadata
Title
Search Guided Saliency
Authors
Shijian Lu
Byung-Uck Kim
Nicolas Lomenie
Joo-Hwee Lim
Jianfei Cai
Copyright Year
2015
Book
Computer Vision - ACCV 2014 Workshops

Print ISBN: 978-3-319-16627-8

Electronic ISBN: 978-3-319-16628-5

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-16628-5_32

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