Block operator context scanning for commercial tracking

Authors:
Ioannis Giannoukos;Vassilis Vrachnakis;Christos-Nikolaos Anagnostopoulos;Ioannis Anagnostopoulos;Vassili Loumos
Affiliations:
Electrical & Computer Engineering School, National Technical University of Athens, Greece;Electrical & Computer Engineering School, National Technical University of Athens, Greece;Cultural Technology and Communication Dpt., University of the Aegean, Greece;Computer Science and Biomedical Informatics Dpt., University of Central Greece, Greece;Electrical & Computer Engineering School, National Technical University of Athens, Greece
Venue:
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Year:
2012

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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.