Face customization in a real-time digiTV stream

The challenge in digital, interactive TV (digiTV) is to move the consumer from the refiguration state to the configuration state, where he can influence the story flow, the choice of characters and other narrative elements. Besides restructuring narrative and interactivity methodologies, one major task is content manipulation to provide the auditorium the ability to predefine actors that it wants to have in its virtual story universe. Current solutions in broadcasting video provide content as monolithic structure, composed of graphics, narration, special effects, etc. compressed into one high bit rate MPEG-2 stream. More personalized and interactive TV requires a contemporary approach to segment video data in real-time to customize contents. Our research work emphasizes techniques for interchanging faces/bodies against virtual anchors in real-time constrained broadcasted video streams. The aim of our research paper is to show and point out solutions for realizing real-time face and avatar customization. The major task for the broadcaster is metadata extraction by applying face detection/tracking/recognition algorithms, and transmission of the information to the client side. At the client side, our system shall provide the facility to pre-select virtual avatars stored in a local database, and synchronize movements and expressions with the current digiTV contents.