USING DEEP LEARNING TECHNOLOGIES TO PROVIDE DESCRIPTIVE METADATA FOR LIVE VIDEO CONTENTS
As the consumption of video contents rises and consumers' behaviour changes, video broadcasters must find new strategies to engage with their viewers. In this context, metadata are used to provide customers with personalized, relevant contents. More recently, content descriptive metadata have enhanced the personalization of services and have offered providers new monetization opportunities thanks to, e.g. more effective content recommendations and contextual advertising. So far, descriptive metadata have been applied to pre recorded contents, while they still represent a huge amount of unexploited valuable information for live streams. This paper highlights how deep learning technologies can add value to information contained in each video frame of both live and non live contents, automatically providing detailed descriptive metadata. This technology opens up the opportunity for broadcasters to offer new services and an innovative way of video consumption.