Games, search engines, e-commerce, infotainment, and many other services allow users a high degree of personalization; this evolution creates new needs, changes habits, and raises expectations. At the same time, the availability of new instruments is noticeably changing the kind of experience the users expect. The strong immersivity and high degree of realism of VR, MR, and AR are freeing the UX from the classic screen borders, with voice and gestures adding naturalness to the experience and keeping high the sense of users’ involvement and immersion.
IoT ecosystems, smartwatches, digital assistants, and other devices, are instruments that may provide precious hints about users and usage contexts, if supported by the application of Pattern Recognition theories and techniques.
Aiming at improving efficiency, intelligence, and delight perceived by users, Pattern Recognition-driven User Experience leverages intelligent computing to dynamically adapt appearance and behaviour with automatic decision-making. Pattern Recognition offers the instruments to detect and “understand” context, user’s signals, intents, emotions, and provides a set of disruptive methodologies for an effective personalization of the experience.
The purpose of this Special Issue is to investigate how concepts and theories related to Pattern Recognition can be applied to improve or create a fully novel User Experience, new opportunities, and open problems. The Special Issue aims at collecting and presenting new advances in the application of Pattern Recognition to (but not limited):
Emotion recognition and adaptive applications; Speech recognition;
Pattern recognition for virtual, augmented and mixed reality;
Applications to mobile and embedded systems;
Natural language applications;
Design and evaluation of innovative interactive system;
Personalization of user experience.
This Special Issue solicits original work that is not under consideration for publication in other journals or conferences. As usual, papers that are extensions of conference papers must present at least 30% of new original contribution in terms of theoretical background and/or experimental studies. In this case the conference paper must be cited and a description of the changes that have been made should be provided in the cover letter as the reason for re-publishing as well as in the paper introduction. No verbatim copies of large blocks of text are allowed. Guest editors will make an initial determination of the suitability and scope of all submissions. The review process will follow the standard PRLetters scheme, with each paper reviewed by at least 2 referees.
SUBMISSION OF MANUSCRIPTS
Authors are encouraged to submit their papers electronically by using online manuscript submission at: http://ees.elsevier.com/prletters/
To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important that authors select the acronym “PRUE” of this special issue when they reach the “Article Type” step in the submission process.
All papers will be rigorously reviewed and will undergo a very competitive selection process.
The Elsevier Editorial System (http://ees.elsevier.com/prletters/) will be set in due time to allow authors to upload their contributions to the special issue in the period January 10, 2021 – February 10, 2021
Important Dates/Tentative schedule Submission deadline: Submission deadline: 10th February 2021
Final Manuscript due: 1st April 2021
Tentative publication date: Springer 2021
For additional information, please contact one of the Guest Editors at the addresses below:
Andrea F. Abate, University of Salerno, Italy ([email protected]) MGE
Giovanni Motta, Google Inc, Mountain View (CA), US ([email protected])
Andrea F. Abate received the Laurea (Summa Cum Laude) in computer science from the University of Salerno, Salerno, Italy, in 1991, and a Ph.D. in applied mathematics and computer science from the University of Pisa, Pisa, Italy, in 1998.
He currently serves as an Associate Professor with the University of Salerno from 2006, where he is Co-Director of the Virtual Reality Laboratory.
Dr. Abate is a member of the IEEE Haptics Technical Committee and a member of the the International Association for Pattern Recognition.
His current research interests include multibiometric systems, virtual/augmented/mixed reality, haptics and human–computer interaction. He has authored many scientific papers published in scientific journals and proceedings of refereed international conferences and co-edited one book. He serves as a reviewer for journals (Elsevier, IEEE, etc) and conferences. He managed as MGE a Special Issue on Pattern Recognition Letters and currently serves as Associate Editor for Pattern Recognition Letters.
Giovanni Motta (S’97 – M’05 – SM’11-17) received the Laurea in Informatica in 1996 (Summa Cum Laude) from University of Salerno, and a PhD in Computer Science from Brandeis University in 2002. He is currently with Google (Assistant) where he works on machine learning and speech recognition. Previous projects at Google include high resolution satellite imagery and analytics, audio streaming and transcoding, audio fingerprinting, and Android infrastructure. Before Google, he lectured at Brandeis and Boston University and worked with several startups and companies such as Bitfone, HP Labs, Qualcomm, HP.
His main interests are in the fields of data compression, coding, algorithms, machine learning, imaging, and speech recognition. He has been granted 16 patents and published two books and more than 50 peer-reviewed papers in journals and conferences. He serves as a reviewer for journals, conferences, and technical publishers, furthermore he is organizer and committee member of several international conferences.