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Visual Content Indexing and Retrieval with Psycho-Visual Models Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Visual Saliency for the Visualization of Digital Paintings

Authors : Pol Kennel, Frédéric Comby, William Puech

Published in: Visual Content Indexing and Retrieval with Psycho-Visual Models

Publisher: Springer International Publishing

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Abstract

Over the last 15 years, several applications have been developed for digital cultural heritage in the image processing and particularly in the area of digital painting. In order to help preserve cultural heritage, this chapter proposes several applications for digital paintings such as restoration, authentication, style analysis and visualization. For the visualization of digital paintings we present specific methods to visualize digital paintings based on visual saliency and in particular we propose an automatic digital painting visualization method based on visual saliency. The proposed system consists of extracting regions of interest (ROI) from a digital painting to characterize them. These close-ups are then animated on the basis of the paintings characteristics and the artist’s or designer’s aim. In order to obtain interesting results from short video clips, we developed a visual saliency map-based method. The experimental results show the efficiency of our approach and an evaluation based on a Mean Opinion Score validates our proposed method.

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previous chapter Image Retrieval Based on Query by Saliency Content
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Metadata
Title
Visual Saliency for the Visualization of Digital Paintings
Authors
Pol Kennel
Frédéric Comby
William Puech
Copyright Year
2017
Book
Visual Content Indexing and Retrieval with Psycho-Visual Models

Print ISBN: 978-3-319-57686-2

Electronic ISBN: 978-3-319-57687-9

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-57687-9_9

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