Abstract
Television can be a prime candidate for bringing internet to masses in an affordable manner, especially in developing nations. One such system available is called home infotainment platform (HIP) that uses an over-the-top box to provide a low-cost and affordable solution. However, user study from HIP suggests that the user experience of browsing internet on TV in a traditional way is not satisfactory. In this paper, we introduce the novel concept of context-aware television implemented on HIP, where we extract TV program contexts like identity and content using image processing techniques of logo detection and character recognition. There can be innovative internet-TV mash-up applications using such contexts. The techniques are especially useful for deriving the contexts from analog broadcast TV content that is prevalent in countries like India. The algorithms are designed in a lightweight manner so that they can be run efficiently on a low-cost resource-constrained platform like HIP. Experimental results with live Indian TV channel data show acceptable accuracy for the proposed systems with low-computational complexity.
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Acknowledgments
The authors thank Prof. Bidyut Baran Chaudhuri and Prof. Utpal Garain from Indian Statistical Institute for their kind advice and suggestions on the algorithm development. The authors also thank Chirabrata Bhaumik and Avik Ghose of TCS Innovation Labs for their help in system implementation of the proposed work on HIP. This work was supported by Innovation Lab, Tata Consultancy Services.
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Pal, A., Chattopadhyay, T., Sinha, A. et al. Context-aware television-internet mash-ups using logo detection and character recognition. Pattern Anal Applic 18, 191–205 (2015). https://doi.org/10.1007/s10044-014-0422-6
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DOI: https://doi.org/10.1007/s10044-014-0422-6