Live Sports Video Analytics Using RTMP-HLS Phase Difference
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Solution Overview
Problem
Existing systems for analyzing live video broadcast streams of sporting events require complex hardware and sophisticated techniques to accurately track players and deliver real-time contextual interactive content, often failing to provide accurate data due to insufficient viewing angles and dynamic images, leading to increased costs and time delays.
Innovation Solution
A sports analytics system that utilizes a computer server with a video demuxer to split live streams into real-time messaging and HTTP streams, employing detection, tracking, recognition, and transmission modules to process frames within the frame persistence time, using phase difference for real-time analysis and overlaying interactive content without overlapping existing graphics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion capture methods using optical systems and sensors are used to track players, then player location measurement accuracy is improved, but system complexity and hardware requirements increase significantly
Solution Approach 1:
The patent uses computer vision technology to create virtual copies or representations of players from video frames, replacing the need for physical sensors and optical measurement systems. The system processes video images to generate player location data, effectively copying the measurement function from physical sensors to software-based image analysis.
Solution Approach 2:
The patent replaces mechanical and optical measurement systems (sensors, cameras, 3D measuring devices) with a software-based computer vision system that processes standard video feeds. This substitution eliminates the need for complex hardware while maintaining player tracking capability through algorithmic analysis of video frames.
2Measurement precision
If multiple cameras and sensors are deployed to capture player data, then data accuracy is improved, but cost and system complexity increase
Solution Approach 1:
The patent makes the existing broadcast camera system perform multiple functions: it captures both the live video feed for broadcasting and the player tracking data for analytics. The same video frames are used for both entertainment purposes and analytical purposes, eliminating the need for separate dedicated tracking cameras and sensors.
Solution Approach 2:
The system creates multiple uses from a single video source by copying the video feed for different purposes: one copy for broadcasting and another copy for analytical processing. This allows the same hardware to serve dual functions without requiring additional cameras.
3Productivity
If complex data tracking and analysis is performed in real-time, then contextual interactive content delivery is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing video frames and pre-identifying player positions and characteristics before the actual analytics delivery is needed. The system prepares player tracking data, video frame analysis, and contextual information in advance, so that when interactive content needs to be delivered, the processing is already complete or near-complete.
Solution Approach 2:
The system maintains continuous processing of video frames and player tracking throughout the broadcast, rather than performing batch processing. This continuous action ensures that player location and contextual data are always up-to-date and ready for immediate delivery, eliminating processing delays when interactive content is requested.
4Productivity
If traditional broadcasting methods are used without real-time analysis, then system simplicity is maintained, but viewer engagement and monetization potential decrease
Solution Approach 1:
The patent introduces an intermediary layer of computer vision processing between the existing broadcast infrastructure and the analytics delivery system. This intermediary processes video frames to extract player information, which is then used to enhance viewer engagement through interactive content, without requiring fundamental changes to either the broadcasting or analytics sides.
Data Source
AI summary
A method and a sports analytics system (SAS) for analyzing a live video broadcast stream (LVBS) of a sporting event are provided. The SAS splits the LVBS into a real time messaging protocol (RTMP) stream and a hypertext transfer protocol live stream (HLS) and analyses the RTMP stream using a phase difference between the RTMP stream and the HLS. The SAS detects persons present in a frame of the RTMP stream using a first set of cues and tracks the detected persons by analyzing preceding frames. The SAS recognizes the tracked persons using a second set of cues, assigns individual weights to each of the second set of cues, and compares the assigned weights of each of the recognized persons with pre-existing data of all players to identify the players in the frame. The SAS transmits the HLS and contextual interactive content of the identified players to a user device.