Video Data FOV Precomputation for Bandwidth Reduction
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Solution Overview
Problem
Current methods for seamless transitions between perspectives in 360° videos are inefficient, leading to high resource usage and scalability issues due to real-time calculation and unnecessary bandwidth consumption, particularly on devices with limited resources.
Innovation Solution
Precomputing and storing static and dynamic FOV datasets allows for efficient streaming of only the requested video data, eliminating the need for real-time processing on both the server and client, and enabling seamless transitions without additional client processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If complete video material is transmitted to the client for FOV calculation, then the client can determine the requested field of view, but bandwidth is used unnecessarily and resource requirements increase
Solution Approach 1:
The patent extracts and transmits only the necessary video data for the requested FOV to the client, removing unnecessary video data that would otherwise be transmitted. This extraction approach allows the client to determine the requested field of view while significantly reducing bandwidth consumption by sending only relevant video segments.
Solution Approach 2:
The system performs preliminary processing on the server side to pre-determine and prepare video data for specific FOVs before transmission. By calculating and preparing the requested field of view in advance on the server, the system eliminates the need to transmit complete video material, thereby reducing bandwidth usage while maintaining client-side determination capability.
2Ease of operation
If complete video material is transmitted to the client, then the client can process the FOV, but resource requirements (memory, CPU/GPU, energy) increase
Solution Approach 1:
The patent extracts only the essential video data corresponding to the requested FOV for transmission to the client. By removing unnecessary video content from the transmission, the client receives minimal data that requires less memory, processing power, and energy to handle, while still maintaining the capability to process the FOV.
Solution Approach 2:
The server performs preliminary FOV determination and video data preparation before transmission. This preliminary action reduces the processing burden on the client by providing pre-processed video data that requires minimal additional client-side computation, thereby reducing memory, CPU/GPU, and energy requirements.
3Measurement precision
If server performs real-time FOV calculation for each client, then the requested video data can be provided accurately, but scalability deteriorates with growing number of clients
Solution Approach 1:
The patent merges the FOV calculation and video data preparation processes into a unified server-side operation. By combining these functions on the server, the system can efficiently handle multiple client requests without requiring each client to perform separate calculations, thereby maintaining accurate FOV data provision while improving scalability to support growing numbers of clients.
Solution Approach 2:
The server performs preliminary FOV calculation and video data preparation in advance before client requests arrive. This preliminary action allows the system to pre-compute and store video data for various FOVs, enabling rapid response to multiple client requests without real-time calculation overhead, thus maintaining accuracy while enhancing scalability.
Data Source
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AI summary
The invention relates to a processing method for video data, which is displayable on at least one display device, characterized in that a) a predetermined quantity of static FOV data sets (6, 8) are precalculated and saved from the video data, b) further video data is calculated and saved for the temporal transitions between the saved static FOV data sets (6, 8) as dynamic FOV data sets (7) (transition data), wherein immediately or at a later time c) a static or dynamic initial FOV data set and a static or dynamic target FOV data set is specifically selected, in particular by a user, and d) the video data corresponding to the selected FOV data sets, including the dynamic transition data between initial FOV and target FOV, are streamable or are streamed. The invention further relates to a processing system and to a client device.