Paper Info
Title
Energy conservation by adaptive feature loading for mobile content-based image retrieval
Abstract
We present an adaptive loading scheme to save energy for content based image retrieval (CBIR) in a mobile system. In CBIR, images are represented and compared by high-dimensional vectors called features. Loading these features into memory and comparing them consumes a significant amount of energy. Our method adaptively reduces the features to be loaded into memory for each query image. The reduction is achieved by estimating the difficulty of the query and by reusing cached features in memory for subsequent queries. We implement our method on a PDA and obtain overall energy reduction of 61.3% compared with an existing CBIR implementation.
Year
DOI
Venue
2008
10.1145/1393921.1393963
ISLPED
Keywords
Field
DocType
query image,adaptive loading scheme,subsequent query,energy conservation,mobile content-based image retrieval,overall energy reduction,mobile system,method adaptively,existing cbir implementation,adaptive feature loading,image retrieval,high-dimensional vector,cached feature,indexes,mobile communication,accuracy,mobile computing,feature extraction
Mobile computing,Energy conservation,Computer science,Cache,Image retrieval,Real-time computing,Artificial intelligence,Computer vision,Pattern recognition,Reuse,Feature extraction,Content-based image retrieval,Mobile telephony
Conference
Citations 
PageRank 
References 
8
0.55
9
Authors
4
Name
Order
Citations
PageRank
Karthik Kumar186338.37
Yamini Nimmagadda2513.63
Yu-Ju Hong3998.29
Yung-Hsiang Lu42165161.51