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
ASIFT: A New Framework for Fully Affine Invariant Image Comparison
SIAM Journal on Imaging Sciences
Partition min-hash for partial duplicate image discovery
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Scalable logo recognition in real-world images
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Three things everyone should know to improve object retrieval
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Correlation-based burstiness for logo retrieval
Proceedings of the 20th ACM international conference on Multimedia
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
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We present a scalable logo recognition technique based on feature bundling. Individual local features are aggregated with features from their spatial neighborhood into bundles. These bundles carry more information about the image content than single visual words. The recognition of logos in novel images is then performed by querying a database of reference images. We further propose a novel WGC-constrained RANSAC and a technique that boosts recall for object retrieval by synthesizing images from original query or reference images. We demonstrate the benefits of these techniques for both small object retrieval and logo recognition. Our logo recognition system clearly outperforms the current state-of-the-art with a recall of 83% at a precision of 99%.