Client-Driven Personalized Trailer Framework Using Thumbnail Containers

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.