Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Efficient Maximally Stable Extremal Region (MSER) Tracking
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Matching sets of features for efficient retrieval and recognition
Matching sets of features for efficient retrieval and recognition
HOTPAPER: multimedia interaction with paper using mobile phones
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Embedded media markers: marks on paper that signify associated media
Proceedings of the 15th international conference on Intelligent user interfaces
Embedded media marker: linking multimedia to paper
Proceedings of the 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
Accelerating SURF detector on mobile devices
Proceedings of the 20th ACM international conference on Multimedia
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We present a large-scale Embedded Media Marker (EMM) identification system which 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 variation in camera-phone-captured query images, we introduce a novel image matching scheme based on geometrically consistent correspondences. A hierarchical scheme, combined with two constraining methods, is designed to detect geometric constrained correspondences between images. A spatial neighborhood search approach is further proposed to address challenging cases of query images with a large translational shift. Experimental results on a 200k+ dataset show that our solution achieves high accuracy with low memory and time complexity and outperforms the baseline bag-of-words approach.