Abstract

Movie trailers are prepared using a one-size-fits-all framework. These days, however, streaming platforms seek to overcome this problem and provide personalized trailers via the investigation of centralized server-side solutions. This can be achieved by analyzing personal user data, and can lead to two major issues: privacy violation and enormous demand in computational resources. This paper proposes an innovative, low-power, client-driven method to facilitate the personalized trailer generation process. It tackles the complex process of detecting personalized actions in real-time from lightweight thumbnail containers. The HTTP live streaming (HLS) server and client are locally configured to validate the proposed method. The system is designed to support a wide range of client hardware with different computational capabilities and has the flexibility to adapt to network conditions. To test the effectiveness of this method, twenty-five broadcast movies, specifically in the western and sports genres, are evaluated. To the best of our knowledge, this is the first-ever client-driven framework that uses thumbnail containers as input to facilitate the trailer generation process.

Highlights

  • Arecent study showed that every day, adults in the US spend nearly six hours watching movies [1]

  • This paper proposes a real-time and low-power client-driven method to facilitate the personalized trailer generation process

  • The main contributions of this paper are concluded : (1) We propose a firstever thumbnail container-based client-driven framework to detect personalized actions in order to expedite and facilitate the trailer generation process

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Summary

Introduction

Arecent study showed that every day, adults in the US spend nearly six hours watching movies [1]. This paper proposes a real-time and low-power client-driven method to facilitate the personalized trailer generation process. To test the effectiveness of the method, the personalized actions in 25 broadcast movies, in the western and sports genres, were identified and evaluated, and subjective evaluation was conducted to compare the number of relevant actions available in official and generated trailers.

Results
Conclusion
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