Paper Info
Title
Demonstration of an Open Source Framework for Qualitative Evaluation of CBIR Systems.
Abstract
Evaluating image retrieval systems in a quantitative way, for example by computing measures like mean average precision, allows for objective comparisons with a ground-truth. However, in cases where ground-truth is not available, the only alternative is to collect feedback from a user. Thus, qualitative assessments become important to better understand how the system works. Visualizing the results could be, in some scenarios, the only way to evaluate the results obtained and also the only opportunity to identify that a system is failing. This necessitates developing a User Interface (UI) for a Content Based Image Retrieval (CBIR) system that allows visualization of results and improvement via capturing user relevance feedback. A well-designed UI facilitates understanding of the performance of the system, both in cases where it works well and perhaps more importantly those which highlight the need for improvement. Our open-source system implements three components to facilitate researchers to quickly develop these capabilities for their retrieval engine. We present: a web-based user interface to visualize retrieval results and collect user annotations; a server that simplifies connection with any underlying CBIR system; and a server that manages the search engine data. The software itself is described in a separate submission to the ACM MM Open Source Software Competition.
Year
DOI
Venue
2018
10.1145/3240508.3241395
MM '18: ACM Multimedia Conference Seoul Republic of Korea October, 2018
Keywords
Field
DocType
ACM proceedings, LATEX, Visualization tool, image retrieval, visual searching, relevance feedback, annotation tool
Relevance feedback,Search engine,Information retrieval,Visualization,Computer science,Image processing,Image retrieval,Software,User interface,Multimedia,Content-based image retrieval
Conference
ISBN
Citations 
PageRank 
978-1-4503-5665-7
0
0.34
References 
Authors
2
5
Name
Order
Citations
PageRank
Paula Gómez Duran100.34
Eva Mohedano2556.81
McGuinness Kevin331436.70
Xavier Giró428832.23
Noel E. O'Connor52137223.20