The big data era has brought with it new challenges to computer vision and image understanding. More scalable and robust methods are required to efficiently index, retrieve, organize and interact with big visual data. One can only think to the amount of image/video data downloaded every minute in social media or to the number of surveillance cameras installed in our cities nowadays. Both cases are not manageable without automatic or semi-automatic (e.g., human-in-the-loop) approaches capable of distill useful information from a large quantity of raw data. This special issue covers a wide range of topics, with a common denominator devoted to the analysis for understanding of images and videos. Some of these papers are extended versions of the best works presented at the International Conference on Image Analysis and Processing ICIAP 2015, held in Genova in September 2015
Computer Vision and Image Understanding
Volume 156, Pages 1-186 (March 2017)
Image and Video Understanding in Big Data
Edited by Vittorio Murino, Shaogang Gong, Chen Change Loy and Loris Bazzani
The issue is available electronically on Science Direct at the following link: http://www.sciencedirect.com/science/journal/10773142/156
The printed special issue will appear in Mar 2017.
Vittorio Murino, Istituto Italiano di Tecnologia, Genova/University of Verona, Verona, Italy
Shaogang Gong, Queen Mary University of London, UK
Chen Change Loy, The Chinese University of Hong Kong, China
Loris Bazzani