RIMS: A Real-time and Intelligent Monitoring System for live-broadcasting platforms

Abstract

Personal live shows on Internet streaming platform currently is blooming as a popular application and attracting several millions of users. The content supervision of live streaming platform, in which hundreds of show rooms perform synchronously, is a major concern with the development of this new kind of service. Traditional image captures and real-time content analysis experience huge difficulties, such as processing delay, data overwhelming and analysis overhead. In this paper, we propose several novel methods and algorithms to monitor real-time live stream and identify illegal live misbehavior intelligently based on state of perception and frame difference analysis. The proposed system makes use of several indicators of the chatting room status rather than analyzing images solely and directly. Three kinds of detecting techniques are adopted: self-adaptive threshold-based abnormal traffic detection, sensitive comments perception, and state evaluation. The proposed system captures the segmentation of video scenes by frame difference analysis, and pays more attention on the showing room that has large scene changes. We deploy our system to monitor a typical live platform called panda.tv, and the overall accuracy of three indicators reaches 90.1%. The application of this system can change current situation where the live platform supervision totally depends on manual review. The key techniques in this system can be widely employed in many applications, such as live broadcast platform industries, video surveillance for state security, and the national security for counter-terrorism.

The evolutionary game analysis of the decision-making behavior of live streaming stakeholders under the value co-creation

“…From a stakeholder perspective, Chen et al [1] discussed the intrinsic mechanism of live Internet broadcasting governance under the participation of multiple parties and proposed corresponding network governance strategies in conjunction with game theory analysis. From a content supervision perspective, Li et al [12] proposed a system to intelligently monitor the misconduct of illegal live broadcasts, which entails the manual review of live streaming content. From the perspective of live streaming platforms, a method to improve user experience was proposed that entails resolving specific problems, such as the broadcast delay between video recording and viewing on Internet live streaming platforms and the synchronization of playback between clients.…”

ABR optimization for live sports events with ICN‐enabled network framework

“…The competition contents are regarded as the heart of live sports events, and the hot events and regular events exist the relatively large differences, including the amount of display and the user base. This puts demands on the live platform in terms of the data retrieval ability, which directly determines whether the live platform can provide the high‐definition, smooth and synchronous live competition services 2 . Although the current proposals on the data retrieval of live video streaming have achieved the good effect, there always exist some challenges, such as the long search time and the incompatibility among different protocols.…”

LSEA: Software-Defined Networking-Based QoS-Aware Routing Mechanism for Live-Soccer Event Applications in Smart Cities

“…At the same time, some burgeoning applications have been emerged and changed people's daily life patterns. For example, there have been a lot of live-broadcasting platforms [6], such as TikTok, Livestream, Twitch, and You-Tube, and these platforms are used to spread some popular programmes. In particular, the live-soccer event applications [7] account for the large proportion of improving the people's enjoyment of life to a great extent, and the classical and well-known representatives are the Europe five major league matches [8] and FIFA world cup [9].…”