Title :
Compact hash codes and data structures for efficient mobile visual search
Author :
Ercoli, Simone ; Bertini, Marco ; Del Bimbo, Alberto
Author_Institution :
MICC, Univ. degli Studi di Firenze, Florence, Italy
fDate :
June 29 2015-July 3 2015
Abstract :
In this paper we present an efficient method for mobile visual search that exploits compact hash codes and data structures for visual features retrieval. The method has been tested on a large scale standard dataset of one million SIFT features, showing a retrieval performance comparable or superior to state-of-the-art methods, and a very high efficiency in terms of memory consumption and computational requirements. These characteristics make it suitable for application to mobile visual search, where devices have limited computational and memory capabilities.
Keywords :
data structures; feature extraction; image retrieval; mobile computing; smart phones; SIFT feature; compact hash codes; computational requirements; data structures; memory consumption; mobile visual search; scale-invariant feature transform; visual features retrieval; Data structures; Databases; Memory management; Standards; Vector quantization; Visualization; Mobile visual search; SIFT; hashing; nearest neighbor search;
Conference_Titel :
Multimedia & Expo Workshops (ICMEW), 2015 IEEE International Conference on
Conference_Location :
Turin
DOI :
10.1109/ICMEW.2015.7169856