Abstract
The industry that designs and promotes advertising products in television channels is constantly growing. For effective market analysis and contract validation, various commercial tracker systems are employed. However, these systems mostly rely on heuristics and, since commercial broadcasting varies significantly, are often inaccurate. This paper proposes a commercial tracker system based on the Block Operator Context Scanning (Block - OCS) algorithm, which is both accurate and fast. The proposed method, similar to coarse-to-fine strategies, skips a large portion of the image sequences by focusing only on Regions of Interest. In this paper, a video matching algorithm is also proposed, which compares image sequences using time sliding windows of frames. Experimental results showed 100% accuracy and 50% speed increase compared to traditional block-based processing methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Giannoukos, I., Anagnostopoulos, C.-N., Loumos, V., Kayafas, E.: Operator context scanning to support high segmentation rates for real time license plate recognition. Pattern Recognition 43, 3866–3878 (2010)
Anagnostopoulos, C.N., Anagnostopoulos, I., Kayafas, E., Loumos, V.: A license plate recognition algorithm for Intelligent Transportation System applications. IEEE Transactions on Intelligent Transportation Systems 7(3), 377–392 (2006)
Anagnostopoulos, C., Anagnostopoulos, I., Vergados, D., Kayafas, E., Loumos, V.: Sliding Windows: A software method for real-time inspection in textile surface. Textile Research Journal 74(7), 646–651 (2004)
Chiu, D.M., Jain, R.: Analysis of the increase and decrease algorithms for congestion avoidance in computer networks. Computer Networks and ISDN Systems 17, 1–14 (1989)
OpenCV. Open Computer Vision Library (February 1, 2012) http://sourceforge.net/projects/opencv/
MySQL. MySQL relational database management system (February 1, 2012), http://www.mysql.com/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Giannoukos, I., Vrachnakis, V., Anagnostopoulos, CN., Anagnostopoulos, I., Loumos, V. (2012). Block Operator Context Scanning for Commercial Tracking. In: Maglogiannis, I., Plagianakos, V., Vlahavas, I. (eds) Artificial Intelligence: Theories and Applications. SETN 2012. Lecture Notes in Computer Science(), vol 7297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30448-4_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-30448-4_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30447-7
Online ISBN: 978-3-642-30448-4
eBook Packages: Computer ScienceComputer Science (R0)