Block operator context scanning for commercial tracking

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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. © 2012 Springer-Verlag.

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APA

Giannoukos, I., Vrachnakis, V., Anagnostopoulos, C. N., Anagnostopoulos, I., & Loumos, V. (2012). Block operator context scanning for commercial tracking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7297 LNCS, pp. 369–374). https://doi.org/10.1007/978-3-642-30448-4_47

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