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 contributionpeer-review

19 Citations (Scopus)


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
Subtitle of host publication19th International Conference, MMM 2013, Proceedings
EditorsShipeng Li, Abdulmotaleb El Saddik, Meng Wang, Tao Mei, Nicu Sebe, Shuicheng Yan, Richang Hong, Cathal Gurrin
Number of pages11
ISBN (Electronic)9783642357282
ISBN (Print)9783642357275
Publication statusPublished - 7 Jan 2013
Externally publishedYes
Event19th International Conference on Advances in Multimedia Modeling - Huangshan, China
Duration: 7 Jan 20139 Jan 2013
Conference number: 19

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


Conference19th International Conference on Advances in Multimedia Modeling
Abbreviated titleMMM 2013


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