Top

Published in:

2018 | OriginalPaper | Chapter

Real-Time Brand Logo Recognition

Authors : Leonardo Bombonato, Guillermo Camara-Chavez, Pedro Silva

Published in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The increasing popularity of Social Networks makes change the way people interact. These interactions produce a huge amount of data and it opens the door to new strategies and marketing analysis. According to Instagram (https://instagram.com/press/) and Tumblr (https://www.tumblr.com/press), an average of 80 and 59 million photos respectively are published every day, and those pictures contain several implicit or explicit brand logos. The analysis and detection of logos in natural images can provide information about how widespread is a brand. In this paper, we propose a real-time brand logo recognition system, that outperforms all other state-of-the-art methods for the challenging FlickrLogos-32 dataset. We experimented with 5 different approaches, all based on the Single Shot MultiBox Detector (SSD). Our best results were achieved with the SSD 512 pretrained, where we outperform by 2.5% of F-score and by 7.4% of recall the best results on this dataset. Besides the higher accuracy, this approach is also relatively fast and can process with a single Nvidia Titan X 19 images per second.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Knowledge Transfer for Writer Identification

next chapter Retinal Vessels Segmentation Based on a Convolutional Neural Network

Bianco, S., Buzzelli, M., Mazzini, D., Schettini, R.: Logo recognition using CNN features. In: Murino, V., Puppo, E. (eds.) ICIAP 2015. LNCS, vol. 9280, pp. 438–448. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23234-8_41 CrossRef

Bianco, S., Buzzelli, M., Mazzini, D., Schettini, R.: Deep learning for logo recognition. arXiv preprint arXiv:1701.02620 (2017)

Boia, R., Florea, C.: Homographic class template for logo localization and recognition. In: Paredes, R., Cardoso, J.S., Pardo, X.M. (eds.) IbPRIA 2015. LNCS, vol. 9117, pp. 487–495. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19390-8_55 CrossRef

Chatfield, K., Simonyan, K., Vedaldi, A., Zisserman, A.: Return of the devil in the details: delving deep into convolutional nets. arXiv preprint arXiv:1405.3531 (2014)

Eggert, C., Winschel, A., Lienhart, R.: On the benefit of synthetic data for company logo detection. In: Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, pp. 1283–1286. ACM (2015)

Francesconi, E., Frasconi, P., Gori, M., Marinai, S., Sheng, J.Q., Soda, G., Sperduti, A.: Logo recognition by recursive neural networks. In: Tombre, K., Chhabra, A.K. (eds.) GREC 1997. LNCS, vol. 1389, pp. 104–117. Springer, Heidelberg (1998). https://doi.org/10.1007/3-540-64381-8_43 CrossRef

Hoi, S.C., Wu, X., Liu, H., Wu, Y., Wang, H., Xue, H., Wu, Q.: Logo-net: large-scale deep logo detection and brand recognition with deep region-based convolutional networks. arXiv preprint arXiv:1511.02462 (2015)

Iandola, F.N., Shen, A., Gao, P., Keutzer, K.: Deeplogo: hitting logo recognition with the deep neural network hammer. arXiv preprint arXiv:1510.02131 (2015)

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., Darrell, T.: Caffe: convolutional architecture for fast feature embedding. arXiv preprint arXiv:1408.5093 (2014)

10.

Li, K.W., Chen, S.Y., Su, S., Duh, D.J., Zhang, H., Li, S.: Logo detection with extendibility and discrimination. Multimedia Tools Appl. 72(2), 1285–1310 (2014)CrossRef

11.

Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S.: SSD: single shot multibox detector. arXiv preprint arXiv:1512.02325 (2015)

12.

Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., Berg, A.C.: SSD: single shot MultiBox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21–37. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46448-0_2 CrossRef

13.

Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef

14.

Nesterov, Y.: A method of solving a convex programming problem with convergence rate O(1/k2) (1983)

15.

Oliveira, G., Frazão, X., Pimentel, A., Ribeiro, B.: Automatic graphic logo detection via fast region-based convolutional networks. arXiv preprint arXiv:1604.06083 (2016)

16.

Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. knowl. Data Eng. 22(10), 1345–1359 (2010)CrossRef

17.

Revaud, J., Douze, M., Schmid, C.: Correlation-based burstiness for logo retrieval. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 965–968. ACM (2012)

18.

Romberg, S., Lienhart, R.: Bundle min-hashing for logo recognition. In: Proceedings of the 3rd ACM International Conference on Multimedia Retrieval, pp. 113–120. ACM (2013)

19.

Romberg, S., Pueyo, L.G., Lienhart, R., Van Zwol, R.: Scalable logo recognition in real-world images. In: Proceedings of the 1st ACM International Conference on Multimedia Retrieval, p. 25. ACM (2011)

20.

Yang, F., Bansal, M.: Feature fusion by similarity regression for logo retrieval. In: 2015 IEEE Winter Conference on Applications of Computer Vision (WACV), p. 959. IEEE (2015)

Title: Real-Time Brand Logo Recognition
Authors: Leonardo Bombonato
Guillermo Camara-Chavez
Pedro Silva
Publisher: Springer International Publishing
Book: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Print ISBN: 978-3-319-75192-4

Electronic ISBN: 978-3-319-75193-1

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-75193-1_14

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner