Building a large scale test collection for effective benchmarking of mobile landmark search

Zhiyong Cheng, Jing Ren, Jialie Shen, Haiyan Miao

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review

Abstract

Studying and analyzing system performance is one of the fundamental factors for the related technological advancement in image retrieval. In this paper, we report the construction of a large scale test collection for facilitating robust performance evaluation of mobile landmark image search. Totally, the test collection consists of (1) 355,141 images about 128 landmarks in five cities over 3 continents from Flickr; (2) different kinds of textual features for each image, including surrounding text (e.g. tags), contextual data (e.g. geo-location and upload time), and metadata (e.g. uploader and EXIF); and (3) six types of low-level visual features. For the task of landmark image retrieval evaluation, we also conduct a series of baseline experimental studies on the search performance over different visual queries, which represent different views of a landmark.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 19th International Conference, MMM 2013, Proceedings
Pages36-46
Number of pages11
Volume7733 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event19th International Conference on Advances in Multimedia Modeling, MMM 2013 - Huangshan, China
Duration: 7 Jan 20139 Jan 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7733 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Advances in Multimedia Modeling, MMM 2013
CountryChina
CityHuangshan
Period7/01/139/01/13

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