Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Performance Analysis of a CBIR System on Shared-Memory Systems and Heterogeneous Clusters
CAMP '05 Proceedings of the Seventh International Workshop on Computer Architecture for Machine Perception
Photo-to-Search: Using Camera Phones to Inquire of the Surrounding World
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
Comparison of CBIR Systems with Different Number of Feature Vector Components
SMAP '07 Proceedings of the Second International Workshop on Semantic Media Adaptation and Personalization
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Searching the web with mobile images for location recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
iScope: personalized multi-modality image search for mobile devices
Proceedings of the 7th international conference on Mobile systems, applications, and services
Ranking servers based on energy savings for computation offloading
Proceedings of the 14th ACM/IEEE international symposium on Low power electronics and design
A platform for developing adaptable multicore applications
CASES '09 Proceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems
Automatic image representation and clustering on mobile devices
Journal of Mobile Multimedia
Energy Conservation for Image Retrieval on Mobile Systems
ACM Transactions on Embedded Computing Systems (TECS)
MediaScope: selective on-demand media retrieval from mobile devices
Proceedings of the 12th international conference on Information processing in sensor networks
Personalized multi-modality image management and search for mobile devices
Personal and Ubiquitous Computing
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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.