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. © Springer-Verlag 2013.
CITATION STYLE
Cheng, Z., Ren, J., Shen, J., & Miao, H. (2013). Building a large scale test collection for effective benchmarking of mobile landmark search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7733 LNCS, pp. 36–46). https://doi.org/10.1007/978-3-642-35728-2_4
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