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Memory-Efficient Image Databases for Mobile Visual Search
Jan.-Mar. 2014 (vol. 21 no. 1)
pp. 14-23
David M. Chen, Stanford University
Bernd Girod, Stanford University
Mobile visual search systems compare images against a database for object recognition. If query data is transmitted over a slow network or processed on a congested server, the latency increases substantially. This article shows how on-device database matching guarantees fast recognition regardless of external conditions. The database signatures must be compact because of limited memory, capable of fast comparisons, and discriminative for robust recognition. The authors first describe methods that compress visual word histograms, which require a codebook and decoding compressed signatures. They then describe methods that use residuals to achieve the same accuracy with much smaller codebooks and compressed domain matching.
Index Terms:
Databases,Histograms,Mobile computing,Image coding,Random access memory,Database management,Vocabulary,Multimedia communication,feature descriptors,multimedia,visual search,augmented reality,image databases,compact signatures,bag of words
Citation:
David M. Chen, Bernd Girod, "Memory-Efficient Image Databases for Mobile Visual Search," IEEE Multimedia, vol. 21, no. 1, pp. 14-23, Jan.-Mar. 2014, doi:10.1109/MMUL.2013.46
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