Special Issue "Visual Information Retrieval"

Guest Editor
Prof. Dr. Pietro Pala
Dipartimento Sistemi e Informatica, Università di Firenze, Via S. Marta, 3, 50139 Firenze, Italy
E-Mail: pala@dsi.unifi.it
Phone: +39 055 4796416
Fax: +39 055 4796493
Interests: content based retrieval of images and video; visual concepts extractions in images and videos; indexing structures for content based retrieval; retrieval of 3D models; segmentation of 3D models; 3D face recognition

Dear Colleagues,

Thanks to the advances in compression and storage technologies, massive amounts of image and video material are produced daily in a broad range of different application contexts such as biomedicine, social networks, cultural heritage and digital libraries. Once it has been stored, the potential of this material largely depends on the availability of models and tools for making it accessible effectively and efficiently to different users matching different profiles. The development of paradigms and theories to address this challenging issue has been the goal of visual information retrieval research that now builds upon consolidated models defined in the last decade to face new challenges in the design of usable system interfaces and interaction paradigms for querying, browsing and summarization, the definition of models for learning visual concepts from large and unstructured image and video collections, the definition of indexing structures to enable efficient access to local and distributed repositories.

The purpose of this Special Issue is to bring together a number of research papers for providing a representative view of the frontier of this research field. Original, high quality papers are solicited that address challenging issues in the field of visual information retrieval, including

• Large-scale and web-scale indexing and retrieval of visual information
• Integration of content, meta data and social network
• Scalable and distributed search
• Novel interfaces and interaction paradigms for search and retrieval of visual information
• Visual content descriptors and similarity metrics
• Indexing algorithms
• Machine learning for visual concept learning and detection
• Large-scale summarization and visualization
• Performance evaluation
• Navigation and browsing on the Web
• Visual information retrieval systems and applications

Submission

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. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as 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 refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed Open Access quarterly 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 500 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Categories and Subject Descriptors:

• H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval
• I.2.6 [Artificial Intelligence]: Learning
• I.4.9 [Image Processing and Computer Vision]: Applications

Additional Keywords:

• visual information retrieval
• image search
• video retrieval
• image databases
• image and video indexing
• human-computer interaction
• visual concepts learning in social media