Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

Authors: Ardizzone, E., Bruno, A. and Gugliuzza, F.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 10485 LNCS

Pages: 191-201

eISSN: 1611-3349

ISBN: 9783319685472

ISSN: 0302-9743

DOI: 10.1007/978-3-319-68548-9_18

Abstract:

Visual Saliency aims to detect the most important regions of an image from a perceptual point of view. More in detail, the goal of Visual Saliency is to build a Saliency Map revealing the salient subset of a given image by analyzing bottom-up and top-down factors of Visual Attention. In this paper we proposed a new method for Saliency detection based on colour and scale analysis, extending our previous work based on SIFT spatial density inspection. We conducted several experiments to study the relationships between saliency methods and the object attention processes and we collected experimental data by tracking the eye movements of thirty viewers in the first three seconds of observation of several images. More precisely, we used a dataset that consists of images with an object in the foreground on an homogeneous background. We are interested in studying the performance of our saliency method with respect to the real fixation maps collected during the experiments. We compared the performances of our method with several state of the art methods with very encouraging results.

https://eprints.bournemouth.ac.uk/34242/

Source: Scopus

Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

Authors: Ardizzone, E., Bruno, A. and Gugliuzza, F.

Journal: IMAGE ANALYSIS AND PROCESSING (ICIAP 2017), PT II

Volume: 10485

Pages: 191-201

eISSN: 1611-3349

ISBN: 978-3-319-68547-2

ISSN: 0302-9743

DOI: 10.1007/978-3-319-68548-9_18

https://eprints.bournemouth.ac.uk/34242/

Source: Web of Science (Lite)

Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

Authors: Ardizzone, E., Bruno, A. and Gugliuzza, F.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 10485 LNCS

Pages: 191-201

DOI: 10.1007/978-3-319-68548-9_18

https://eprints.bournemouth.ac.uk/34242/

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032474250&doi=10.1007%2f978-3-319-68548-9_18&partnerID=40&md5=dcaf37865df5d81695aa97095474c11a

Source: Manual

Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

Authors: Ardizzone, E., Bruno, A. and Gugliuzza, F.

Journal: Lecture Notes in Computer Science

Volume: 10485

Pages: 191-201

ISSN: 0302-9743

Abstract:

Visual Saliency aims to detect the most important regions of an image from a perceptual point of view. More in detail, the goal of Visual Saliency is to build a Saliency Map revealing the salient subset of a given image by analyzing bottom-up and top-down factors of Visual Attention. In this paper we proposed a new method for Saliency detection based on colour and scale analysis, extending our previous work based on SIFT spatial density inspection. We conducted several experiments to study the relationships between saliency methods and the object attention processes and we collected experimental data by tracking the eye movements of thirty viewers in the first three seconds of observation of several images. More precisely, we used a dataset that consists of images with an object in the foreground on an homogeneous background. We are interested in studying the performance of our saliency method with respect to the real fixation maps collected during the experiments. We compared the performances of our method with several state of the art methods with very encouraging result

https://eprints.bournemouth.ac.uk/34242/

https://www.springer.com/gb/computer-science/lncs

Source: BURO EPrints