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J. Imaging
Special Issues
Multimedia Content Analysis and Applications
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Multimedia Content Analysis and Applications

A special issue of Journal of Imaging (ISSN 2313-433X).

Deadline for manuscript submissions: closed (31 October 2018)

Special Issue Editors

Prof. Gianluigi Ciocca

E-Mail Website
Guest Editor
Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126 Milano, Italy
Interests: computer vision; image understanding; pattern recognition; video analysis; multimedia systems
Dr. Francesca Gasparini

E-Mail Website
Guest Editor
Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126 Milano, Italy
Interests: multimedia signal processing; image quality assessment; image complexity; affective signal processing
Special Issues, Collections and Topics in MDPI journals
Dr. Silvia Corchs

E-Mail Website
Guest Editor
Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126 Milano, Italy
Interests: multimedia signal processing; affective computing; multi modal data; emotional states; image quality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent years have witnessed the unprecedented booming of media content creation thanks to the availability of a plethora of different imaging devices and also to the growth of public platforms where people store, share, and comment images and videos. How manage this amount of data in a user-friendly way? Content analysis can be a key component for creating systems and applications that allow users to organize, browse, retrieve, and share their creations. Many research efforts have been devoted to these aspects, and with the new era of machine learning, many challenges seem to be achievable. This Special Issue is focused on recent trends in the field of multimedia content analysis such as new research results, as well as the development of new applications. Topics of interest include, but are not limited to, the following:

  • Multimedia annotation, search, and retrieval
  • Multimedia signal processing and analysis
  • Image and video indexing
  • Image and video classification
  • Multimedia content analysis and event detection
  • Object and/or context based multimedia information retrieval
  • Bio-inspired multimedia processing
  • Multimodal processing and analysis
  • Multimedia for  Cultural Heritage
  • Content-based analysis for multimedia data
  • Multimedia application
  • Human computer interaction

Papers must present novel results, applications, or significant advancement of previously published work.

Prof. Gianluigi Ciocca
Prof. Francesca Gasparini
Dr. Silvia Elena Corchs
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Multimedia analysis
  • Signal processing
  • Image and video understanding
  • Human computer interaction
  • Multimodal processing
  • Multimedia applications

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Published Papers (2 papers)

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Research

40 pages, 5027 KiB  
Article
Quality Assessment of HDR/WCG Images Using HDR Uniform Color Spaces
by Maxime Rousselot, Olivier Le Meur, Rémi Cozot and Xavier Ducloux
J. Imaging 2019, 5(1), 18; https://doi.org/10.3390/jimaging5010018 - 14 Jan 2019
Cited by 20 | Viewed by 8242
Abstract
High Dynamic Range (HDR) and Wide Color Gamut (WCG) screens are able to render brighter and darker pixels with more vivid colors than ever. To assess the quality of images and videos displayed on these screens, new quality assessment metrics adapted to this [...] Read more.
High Dynamic Range (HDR) and Wide Color Gamut (WCG) screens are able to render brighter and darker pixels with more vivid colors than ever. To assess the quality of images and videos displayed on these screens, new quality assessment metrics adapted to this new content are required. Because most SDR metrics assume that the representation of images is perceptually uniform, we study the impact of three uniform color spaces developed specifically for HDR and WCG images, namely, I C t C p , J z a z b z and H D R - L a b on 12 SDR quality assessment metrics. Moreover, as the existing databases of images annotated with subjective scores are using a standard gamut, two new HDR databases using WCG are proposed. Results show that MS-SSIM and FSIM are among the most reliable metrics. This study also highlights the fact that the diffuse white of HDR images plays an important role when adapting SDR metrics for HDR content. Moreover, the adapted SDR metrics does not perform well to predict the impact of chrominance distortions. Full article
(This article belongs to the Special Issue Multimedia Content Analysis and Applications)
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14 pages, 9409 KiB  
Article
User-Centered Predictive Model for Improving Cultural Heritage Augmented Reality Applications: An HMM-Based Approach for Eye-Tracking Data
by Roberto Pierdicca, Marina Paolanti, Simona Naspetti, Serena Mandolesi, Raffaele Zanoli and Emanuele Frontoni
J. Imaging 2018, 4(8), 101; https://doi.org/10.3390/jimaging4080101 - 6 Aug 2018
Cited by 10 | Viewed by 5481
Abstract
Today, museum visits are perceived as an opportunity for individuals to explore and make up their own minds. The increasing technical capabilities of Augmented Reality (AR) technology have raised audience expectations, advancing the use of mobile AR in cultural heritage (CH) settings. Hence, [...] Read more.
Today, museum visits are perceived as an opportunity for individuals to explore and make up their own minds. The increasing technical capabilities of Augmented Reality (AR) technology have raised audience expectations, advancing the use of mobile AR in cultural heritage (CH) settings. Hence, there is the need to define a criteria, based on users’ preference, able to drive developers and insiders toward a more conscious development of AR-based applications. Starting from previous research (performed to define a protocol for understanding the visual behaviour of subjects looking at paintings), this paper introduces a truly predictive model of the museum visitor’s visual behaviour, measured by an eye tracker. A Hidden Markov Model (HMM) approach is presented, able to predict users’ attention in front of a painting. Furthermore, this research compares users’ behaviour between adults and children, expanding the results to different kind of users, thus providing a reliable approach to eye trajectories. Tests have been conducted defining areas of interest (AOI) and observing the most visited ones, attempting the prediction of subsequent transitions between AOIs. The results demonstrate the effectiveness and suitability of our approach, with performance evaluation values that exceed 90%. Full article
(This article belongs to the Special Issue Multimedia Content Analysis and Applications)
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