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J. Imaging
Special Issues
Image/Video Processing and Coding
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Image/Video Processing and Coding

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

Deadline for manuscript submissions: closed (18 October 2019) | Viewed by 15931

Special Issue Editor

Dr. Cataldo Guaragnella

E-Mail Website
Guest Editor
Dipartimento di Ingegneria Elettrica e dell’Informazione, Politecnico di Bari, Via E. Orabona 4, 70125 Bari, Italy
Interests: signal processing; signal; image and video coding; pattern recognition; multidimensional signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

All media faces the general problem of the coding of the information for transmission to the final user, this is a particular problem in relation to the emergence of new media, mobile media and social media, and the general and diffuse use of short videos in many social and crowdsourced information systems, the advent of stereo/multiview vision systems and the availability of RGB-D cameras in vision systems, able to reproduce 3D objects in the scene. Video compression techniques, formerly defined as techniques and algorithms able to provide efficient solutions to represent video data in a compact form to be delivered in a cost-effective way through a given communication link to a destination site, recently have shifted to assume a more complex definition in which many different approaches are adopted to solve the specific problem of optimization in the information interchange between peers or in broadcasting networks. This optimization is influenced by the quality of the received video, the data rate required to transmit the information, the device power consumption, the algorithm complexity, the scalability and the general quality of experience in the creation of videos.

The general problem of coding is always getting more challenging because several coding techniques have to coexist in different application scenarios. Even if there is plenty of video coding systems that perform well in specific applications, the unitary description of the problem of video coding is still far from being defined; its domain can be located in a multidimensional space in which different videos with different characteristics in terms of frame rates, resolutions, duration, bandwidths, contribute to the specific application framework to allow the definition of new and fascinating applications.

Submissions to this Special Issue on Image/Video Processing and Coding are solicited to represent a snapshot of the field’s development by covering a range of topics that include, but are not limited to, new methods, algorithms, solutions and applications in the areas:

  • Image/video analysis
  • Semantic information extraction in video
  • Action analysis, recognition and coding in video
  • Video coding algorithms
  • High-efficiency video coding
  • Multiview video coding
  • 3D video analysis/processing/coding
  • Content-based video coding
  • Stereo video coding
  • Scaleable video coding
  • Predictive video coding
  • Video composition from different sources
  • HW implementation of coding systems
  • Emerging algorithms for image and video processing
  • Model-based video coding
  • Perceptual video coding
  • Statistic-based video coding
  • Deep learning and CNN approaches to video coding
  • Low complexity video coding

Dr. Cataldo Guaragnella
Guest Editor

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

  • Video analysis/coding
  • Multidimensional video
  • Image processing/coding
  • 3D imaging/coding
  • Deep learning for video coding
  • Architecture and systems

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Published Papers (2 papers)

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Research

18 pages, 3455 KiB  
Article
Food Intake Actions Detection: An Improved Algorithm Toward Real-Time Analysis
by Ennio Gambi, Manola Ricciuti and Adelmo De Santis
J. Imaging 2020, 6(3), 12; https://doi.org/10.3390/jimaging6030012 - 17 Mar 2020
Cited by 4 | Viewed by 3750
Abstract
With the increase in life expectancy, one of the most important topic for scientific research, especially for the elderly, is good nutrition. In particular, with an advanced age and health issues because disorders such as Alzheimer and dementia, monitoring the subjects’ dietary habits [...] Read more.
With the increase in life expectancy, one of the most important topic for scientific research, especially for the elderly, is good nutrition. In particular, with an advanced age and health issues because disorders such as Alzheimer and dementia, monitoring the subjects’ dietary habits to avoid excessive or poor nutrition is a critical role. Starting from an application aiming to monitor the food intake actions of people during a meal, already shown in a previously published paper, the present work describes some improvements that are able to make the application work in real time. The considered solution exploits the Kinect v1 device that can be installed on the ceiling, in a top-down view in an effort to preserve privacy of the subjects. The food intake actions are estimated from the analysis of depth frames. The innovations introduced in this document are related to the automatic identification of the initial and final frame for the detection of food intake actions, and to the strong revision of the procedure to identify food intake actions with respect to the original work, in order to optimize the performance of the algorithm. Evaluation of the computational effort and system performance compared to the previous version of the application has demonstrated a possible real-time applicability of the solution presented in this document. Full article
(This article belongs to the Special Issue Image/Video Processing and Coding)
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15 pages, 1471 KiB  
Article
Real-Time System for Driver Fatigue Detection Based on a Recurrent Neuronal Network
by Younes Ed-Doughmi, Najlae Idrissi and Youssef Hbali
J. Imaging 2020, 6(3), 8; https://doi.org/10.3390/jimaging6030008 - 4 Mar 2020
Cited by 58 | Viewed by 11459
Abstract
In recent years, the rise of car accident fatalities has grown significantly around the world. Hence, road security has become a global concern and a challenging problem that needs to be solved. The deaths caused by road accidents are still increasing and currently [...] Read more.
In recent years, the rise of car accident fatalities has grown significantly around the world. Hence, road security has become a global concern and a challenging problem that needs to be solved. The deaths caused by road accidents are still increasing and currently viewed as a significant general medical issue. The most recent developments have made in advancing knowledge and scientific capacities of vehicles, enabling them to see and examine street situations to counteract mishaps and secure travelers. Therefore, the analysis of driver’s behaviors on the road has become one of the leading research subjects in recent years, particularly drowsiness, as it grants the most elevated factor of mishaps and is the primary source of death on roads. This paper presents a way to analyze and anticipate driver drowsiness by applying a Recurrent Neural Network over a sequence frame driver’s face. We used a dataset to shape and approve our model and implemented repetitive neural network architecture multi-layer model-based 3D Convolutional Networks to detect driver drowsiness. After a training session, we obtained a promising accuracy that approaches a 92% acceptance rate, which made it possible to develop a real-time driver monitoring system to reduce road accidents. Full article
(This article belongs to the Special Issue Image/Video Processing and Coding)
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