Scalable triangulation-based logo recognition

We propose a scalable logo recognition approach that extends the common bag-of-words model and incorporates local geometry in the indexing process. Given a query image and a large logo database, the goal is to recognize the logo contained in the query, if any. We locally group features in triples using multi-scale Delaunay triangulation and represent triangles by signatures capturing both visual appearance and local geometry. Each class is represented by the union of such signatures over all instances in the class. We see large scale recognition as a sub-linear search problem where signatures of the query image are looked up in an inverted index structure of the class models. We evaluate our approach on a large-scale logo recognition dataset with more than four thousand classes.

[1]  Ehud Rivlin,et al.  Logo recognition using geometric invariants , 1993, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93).

[2]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[3]  Alan Hanjalic,et al.  Logo detection and classification in a sport video: video indexing for sponsorship revenue control , 2001, IS&T/SPIE Electronic Imaging.

[4]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Matthew A. Brown,et al.  Invariant Features from Interest Point Groups , 2002, BMVC.

[6]  Hanan Samet,et al.  Content-based image retrieval using Fourier descriptors on a logo database , 2002, Object recognition supported by user interaction for service robots.

[7]  Andrew Zisserman,et al.  Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[8]  A. Torralba,et al.  Sharing features: efficient boosting procedures for multiclass object detection , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[9]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[10]  Cordelia Schmid,et al.  Semi-Local Affine Parts for Object Recognition , 2004, BMVC.

[11]  Stepán Obdrzálek,et al.  Sub-linear Indexing for Large Scale Object Recognition , 2005, BMVC.

[12]  Alex Santos Real-Time Opaque and Semi-Transparent TV Logos Detection , 2006 .

[13]  Ling-Yu Duan,et al.  A Robust Method for TV Logo Tracking in Video Streams , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[14]  Luc Van Gool,et al.  Edinburgh Research Explorer Simultaneous Object Recognition and Segmentation by Image Exploration , 2022 .

[15]  Trevor Darrell,et al.  Unsupervised Learning of Categories from Sets of Partially Matching Image Features , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[16]  Michael Isard,et al.  Object retrieval with large vocabularies and fast spatial matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  Ming Yang,et al.  Discovery of Collocation Patterns: from Visual Words to Visual Phrases , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Alberto Del Bimbo,et al.  Trademark matching and retrieval in sports video databases , 2007, MIR '07.

[19]  Hassan Foroosh,et al.  View-invariant action recognition using fundamental ratios , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Xing Xie,et al.  Spatial pyramid mining for logo detection in natural scenes , 2008, 2008 IEEE International Conference on Multimedia and Expo.

[21]  Stella X. Yu,et al.  Linear solution to scale and rotation invariant object matching , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[22]  Olivier Buisson,et al.  Logo retrieval with a contrario visual query expansion , 2009, ACM Multimedia.

[23]  Shin'ichi Satoh,et al.  Indexing local configurations of features for scalable content-based video copy detection , 2009, LS-MMRM '09.

[24]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[25]  David S. Doermann,et al.  Logo Matching for Document Image Retrieval , 2009, 2009 10th International Conference on Document Analysis and Recognition.

[26]  Jiri Matas,et al.  Efficient representation of local geometry for large scale object retrieval , 2009, CVPR.

[27]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Jian Sun,et al.  Bundling features for large scale partial-duplicate web image search , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[29]  Aniruddha Sinha,et al.  Recognition of trademarks from sports videos for channel hyperlinking in consumer end , 2009, 2009 IEEE 13th International Symposium on Consumer Electronics.

[30]  Christopher D. Manning,et al.  Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..

[31]  Zhe Li,et al.  Fast Logo Detection and Recognition in Document Images , 2010, 2010 20th International Conference on Pattern Recognition.

[32]  Yannis Avrithis,et al.  Feature map hashing: sub-linear indexing of appearance and global geometry , 2010, ACM Multimedia.