AuthorsL. Piras, B. Caputo, D. Dang-Nguyen, M. Riegler and P. Halvorsen
EditorsN. Ferro and C. Peters
TitleImage Retrieval Evaluation in Specific Domains
AfilliationMachine Learning
Project(s)Simula Metropolitan Center for Digital Engineering, Department of Holistic Systems
StatusPublished
Publication TypeBook Chapter
Year of Publication2019
Book TitleInformation Retrieval Evaluation in a Changing World - Lessons Learned from 20 Years of CLEF
VolumeINRE, volume 41
Pagination275-305
Publisher Springer
Abstract

Image retrieval was, and still is, a hot topic in research. It comes with many challenges that changed over the years with the emergence of more advanced methods for analysis and enormous growth of images created, shared and consumed. This chapter gives an overview of domain-specific image retrieval evaluation approaches, which were part of the ImageCLEF evaluation campaign . Specifically, the robot vision, photo retrieval, scalable image annotation and lifelogging tasks are presented. The ImageCLEF medical activity is described in a separate chapter in this volume. Some of the presented tasks have been available for several years, whereas others are quite new (like lifelogging). This mix of new and old topics has been chosen to give the reader an idea about the development and trends within image retrieval. For each of the tasks, the datasets, participants, techniques used and lessons learned are presented and discussed leading to a comprehensive summary.

DOI10.1007/978-3-030-22948-1_12

Contact person