Mobile image recognition: architectures and tradeoffs

Authors:
Jonathan J. Hull;Xu Liu;Berna Erol;Jamey Graham;Jorge Moraleda
Affiliations:
Ricoh Innovations, Inc., California Research Center, Menlo Park, CA;Ricoh Innovations, Inc., California Research Center, Menlo Park, CA;Ricoh Innovations, Inc., California Research Center, Menlo Park, CA;Ricoh Innovations, Inc., California Research Center, Menlo Park, CA;Ricoh Innovations, Inc., California Research Center, Menlo Park, CA
Venue:
Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications
Year:
2010

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Abstract

We argue that the most desirable architecture for mobile image recognition runs the complete algorithm on the mobile device. Alternative solutions that run the recognizer on a remote server will not be as desirable because of the delay between image capture and receipt of a result that can cause users to abandon the technique. We present a method for mobile recognition of paper documents and an application to newspapers that lets readers retrieve electronic data linked to articles, photos, and advertisements. We show that the index for a reasonable collection of daily newspapers can be downloaded in less than a minute and will fit in the memory of today's mid-range smart phones. Experimental results show that the recognition system has an overall error rate of less than 1%. We achieved a run time of 1.2 secs. per image with a collection of 140 newspaper pages on an HTC-8282 Windows Mobile phone.