Embedded media markers: marks on paper that signify associated media
Proceedings of the 15th international conference on Intelligent user interfaces
Mobile image recognition: architectures and tradeoffs
Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications
Pacer: fine-grained interactive paper via camera-touch hybrid gestures on a cell phone
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PaperComp 2010: first international workshop on paper computing
Proceedings of the 12th ACM international conference adjunct papers on Ubiquitous computing - Adjunct
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Editorial: Introduction to the special issue on question answering
Information Processing and Management: an International Journal
A survey on question answering technology from an information retrieval perspective
Information Sciences: an International Journal
A tool for authoring unambiguous links from printed content to digital media
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Minimum correspondence sets for improving large-scale augmented paper
Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
Mobile visual aid tools for users with visual impairments
Mobile Multimedia Processing
CBDAR'11 Proceedings of the 4th international conference on Camera-Based Document Analysis and Recognition
Information extraction efficiency of business documents captured with smartphones and tablets
Proceedings of the 2013 ACM symposium on Document engineering
Near-duplicate document image matching: A graphical perspective
Pattern Recognition
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In this paper, we describe an image based document retrieval system which runs on camera enabled mobile devices. “Mobile Retriever” aims to seamlessly link physical and digital documents by allowing users to snap a picture of the text of a document and retrieve its electronic version from a database. Experiments show that for a database of 100,093 pages, the correct document can be retrieved in less than 4 s at a success rate over 95%. Our system extracts token pairs from the text, to efficiently index and retrieve candidate pages using only a small portion of the image. We use token triplets that define the orientation of three corresponding tokens to effectively prune the false positives and identify the correct page to retrieve. We stress the importance of geometrical relationship between feature points and show its effectiveness in our camera based image retrieval system.