Title :
Memory-Efficient Image Databases for Mobile Visual Search
Author :
Chen, D.M. ; Girod, B.
Author_Institution :
Stanford Univ., Stanford, CA, USA
Abstract :
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.
Keywords :
data compression; image coding; image matching; image retrieval; mobile computing; object recognition; query formulation; visual databases; codebook; compressed domain matching; congested server; database signatures; decoding; memory-efficient image databases; mobile visual search systems; object recognition; on-device database matching; query data; signature compression; visual word histograms compression; Database management; Databases; Histograms; Image coding; Mobile computing; Multimedia communication; Random access memory; Vocabulary; augmented reality; bag of words; compact signatures; feature descriptors; image databases; multimedia; visual search;
Journal_Title :
MultiMedia, IEEE
DOI :
10.1109/MMUL.2013.46