Embedded Media Markers

Linking paper documents to online media

Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document.

EMMs also guide users’ camera operations for media retrieval. Users take a picture of an EMM signified document patch using a cell phone, and the media associated with the EMM-signified document location is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document contents. Retrieval of media associated with an EMM is based on image local features of the captured EMMsignified document patch. An EMM is placed semi-automaticallyat a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document.


Embedded Media Markers (ENGLISH)


紙に埋め込み、異なるメディアにリンクするためのマーカ

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Related Publications

2011
Publication Details
  • The 10th International Conference on Virtual Reality Continuum and Its Applications in Industry
  • Dec 11, 2011

Abstract

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Augmented Paper (AP) is an important area of Augmented Reality (AR). Many AP systems rely on visual features for paper doc-ument identification. Although promising, these systems can hardly support large sets of documents (i.e. one million documents) because of the high memory and time cost in handling high-dimensional features. On the other hand, general large-scale image identification techniques are not well customized to AP, costing unnecessarily more resource to achieve the identification accuracy required by AP. To address this mismatching between AP and image identification techniques, we propose a novel large-scale image identification technique well geared to AP. At its core is a geometric verification scheme based on Minimum visual-word Correspondence Set (MICSs). MICS is a set of visual word (i.e. quantized visual fea-ture) correspondences, each of which contains a minimum number of correspondences that are sufficient for deriving a transformation hypothesis between a captured document image and an indexed image. Our method selects appropriate MICSs to vote in a Hough space of transformation parameters, and uses a robust dense region detection algorithm to locate the possible transformation models in the space. The models are then utilized to verify all the visual word correspondence to precisely identify the matching indexed image. By taking advantage of unique geometric constraints in AP, our method can significantly reduce the time and memory cost while achieving high accuracy. As showed in evaluation with two AP systems called FACT and EMM, over a dataset with 1M+ images, our method achieves 100% identification accuracy and 0.67% registration error for FACT; For EMM, our method outperforms the state-of-the-art image identification approach by achieving 4% improvements in detection rate and almost perfect precision, while saving 40% and 70% memory and time cost.
Publication Details
  • ACM Multimedia 2011
  • Nov 28, 2011

Abstract

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Embedded Media Markers (EMMs) are nearly transparent icons printed on paper documents that link to associated digital media. By using the document content for retrieval, EMMs are less visually intrusive than barcodes and other glyphs while still providing an indication for the presence of links. An initial implementation demonstrated good overall performance but exposed difficulties in guaranteeing the creation of unambiguous EMMs. We developed an EMM authoring tool that supports the interactive authoring of EMMs via visualizations that show the user which areas on a page may cause recognition errors and automatic feedback that moves the authored EMM away from those areas. The authoring tool and the techniques it relies on have been applied to corpora with different visual characteristics to explore the generality of our approach.

PaperUI

Publication Details
  • CBDAR 2011
  • Sep 18, 2011

Abstract

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PaperUI is a human-computer interface concept that treats paper as displays that users can interact with via mobile devices such as mobile phones and projectors. It combines the merits of paper and the mobile devices. Compared with traditional laptops and tablet PCs, devices involved in this concept are more light-weight, compact, energy efficient, and widely adopted. Therefore, we believe this interface vision can make computation more convenient to access for general public. With our implemented prototype, pilot users can read documents easily and comfortably on paper, and access many digital functions related to the document via a camera phone or a mobile projector Invited Talk. http://imlab.jp/cbdar2011/#keynote
Publication Details
  • ACM International Conference on Multimedia Retrieval (ICMR) 2011
  • Apr 17, 2011

Abstract

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Embedded Media Marker (EMM) identification system allows users to retrieve relevant dynamic media associated with a static paper document via camera phones. The user supplies a query image by capturing an EMM-signified patch of a paper document through a camera phone; the system recognizes the query and in turn retrieves and plays the corresponding media on the phone. Accurate image matching is crucial for positive user experience in this application. To address the challenges posed by large datasets and variations in camera-phone-captured query images, we introduce a novel image matching scheme based on geometrically consistent correspondences. Two matching constraints - "injection" and "approximate global geometric consistency" (AGGC), which are unique in EMM identification, are presented. A hierarchical scheme, combined with two constraining functions, is designed to detect the "injective-AGGC" correspondences between images. A spatial neighborhood search approach is further proposed to address challenging cases with large translational shift. Experimental results on a 100k+ dataset show that our solution achieves high accuracy with low memory and time complexity and outperforms the standard bag-of-words approach.
Publication Details
  • Fuji Xerox Technical Report
  • Jan 1, 2011

Abstract

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Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document. EMMs also guide users' camera operations for media retrieval. Users take a picture of an EMM-signified document patch using a cell phone, and the media associated with the EMM-signified document location is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document appearance. Retrieval of media associated with an EMM is based on image local features of the captured EMM-signified document patch. This paper describes a technique for semi-automatically placing an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document.
2010
Publication Details
  • ACM Multimedia 2010
  • Oct 25, 2010

Abstract

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An Embedded Media Marker (EMM) is a transparent mark printed on a paper document that signifies the availability of additional media associated with that part of the document. Users take a picture of the EMM using a camera phone, and the media associated with that part of the document is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document appearance. Retrieval of media associated with an EMM is based on image features of the document within the EMM boundary. Unlike other feature-based retrieval methods, the EMM clearly indicates to the user the existence and type of media associated with the document location. A semi-automatic authoring tool is used to place an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document. We will demonstrate how to create an EMM-enhanced document, and how the EMM enables access to the associated media on a cell phone.
Publication Details
  • IEEE Pervasive Computing. 9(2). 46-55.
  • Mar 15, 2010

Abstract

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Paper is static but it is also light, flexible, robust, and has high resolution for reading documents in various scenarios. Digital devices will likely never match the flexibility of paper, but come with all of the benefits of computation and networking. Tags provide a simple means of bridging the gap between the two media to get the most out of both. In this paper, we explore the tradeoffs between two different types of tagging technologies – marker-based and content-based – through the lens of four systems we have developed and evaluated at our lab. From our experiences, we extrapolate issues for designers to consider when developing systems that transition between paper and digital content in a variety of different scenarios.
Publication Details
  • IUI 2010 Best Paper Award
  • Feb 7, 2010

Abstract

Close
Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document. EMMs also guide users' camera operations for media retrieval. Users take a picture of an EMMsignified document patch using a cell phone, and the media associated with the EMM-signified document location is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document contents. Retrieval of media associated with an EMM is based on image local features of the captured EMMsignified document patch. This paper describes a technique for semi-automatically placing an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document.
2009
Publication Details
  • 2009 IEEE International Conference on Multimedia and Expo (ICME)
  • Jun 30, 2009

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This paper presents a tool and a novel Fast Invariant Transform (FIT) algorithm for language independent e-documents access. The tool enables a person to access an e-document through an informal camera capture of a document hardcopy. It can save people from remembering/exploring numerous directories and file names, or even going through many pages/paragraphs in one document. It can also facilitate people’s manipulation of a document or people’s interactions through documents. Additionally, the algorithm is useful for binding multimedia data to language independent paper documents. Our document recognition algorithm is inspired by the widely known SIFT descriptor [4] but can be computed much more efficiently for both descriptor construction and search. It also uses much less storage space than the SIFT approach. By testing our algorithm with randomly scaled and rotated document pages, we can achieve a 99.73% page recognition rate on the 2188-page ICME06 proceedings and 99.9% page recognition rate on a 504-page Japanese math book.

2008
Publication Details
  • ACM Multimedia 2008
  • Oct 27, 2008

Abstract

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This demo introduces a tool for accessing an e-document by capturing one or more images of a real object or document hardcopy. This tool is useful when a file name or location of the file is unknown or unclear. It can save field workers and office workers from remembering/exploring numerous directories and file names. Frequently, it can convert tedious keyboard typing in a search box to a simple camera click. Additionally, when a remote collaborator cannot clearly see an object or a document hardcopy through remote collaboration cameras, this tool can be used to automatically retrieve and send the original e-document to a remote screen or printer.
2006
Publication Details
  • Proceedings of IEEE Multimedia Signal Processing 2006
  • Oct 3, 2006

Abstract

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This paper presents a method for facilitating document redirection in a physical environment via a mobile camera. With this method, a user is able to move documents among electronic devices, post a paper document to a selected public display, or make a printout of a white board with simple point-and-capture operations. More specifically, the user can move a document from its source to a destination by capturing a source image and a destination image in a consecutive order. The system uses SIFT (Scale Invariant Feature Transform) features of captured images to identify the devices a user is pointing to, and issues corresponding commands associated with identified devices. Unlike RF/IR based remote controls, this method uses object visual features as an all time 'transmitter' for many tasks, and therefore is easy to deploy. We present experiments on identifying three public displays and a document scanner in a conference room for evaluation.