Geometric Hashing: An Overview
IEEE Computational Science & Engineering
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
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Trademark matching and retrieval in sports video databases
Proceedings of the international workshop on Workshop on multimedia information retrieval
Indexing local configurations of features for scalable content-based video copy detection
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Logo retrieval with a contrario visual query expansion
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature map hashing: sub-linear indexing of appearance and global geometry
Proceedings of the international conference on Multimedia
From local features to local regions
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Deriving a discriminative color model for a given object class from weakly labeled training data
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
In-video product annotation with web information mining
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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
Bundle min-hashing for logo recognition
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Towards automatic object annotations from global image labels
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
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In this paper we propose a highly effective and scalable framework for recognizing logos in images. At the core of our approach lays a method for encoding and indexing the relative spatial layout of local features detected in the logo images. Based on the analysis of the local features and the composition of basic spatial structures, such as edges and triangles, we can derive a quantized representation of the regions in the logos and minimize the false positive detections. Furthermore, we propose a cascaded index for scalable multi-class recognition of logos. For the evaluation of our system, we have constructed and released a logo recognition benchmark which consists of manually labeled logo images, complemented with non-logo images, all posted on Flickr. The dataset consists of a training, validation, and test set with 32 logo-classes. We thoroughly evaluate our system with this benchmark and show that our approach effectively recognizes different logo classes with high precision.