360-Degree Video Boundary Shifting for Compression
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Solution Overview
Problem
Current methods for encoding 360-degree panoramic video content are inefficient, leading to high data transmission requirements that exceed the capabilities of existing infrastructure, and previous image processing techniques do not optimize compression based on image content.
Innovation Solution
A method involving a multi-camera system and image processor that analyzes and shifts the boundaries of 360-degree images to create a new edge location, improving compression efficiency by identifying areas with fewer spatial and temporal dependencies, thereby optimizing encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If 360-degree panoramic video content is encoded using conventional methods, then the video content can be transmitted, but the data transmission requirements exceed the capabilities of existing infrastructure due to inefficient compression
Solution Approach 1:
The 360-degree video content is divided into multiple regions or segments for separate encoding. The encoder processes different portions of the panoramic video with different compression strategies, allowing more efficient overall compression by treating homogeneous regions separately rather than as a single large block.
Solution Approach 2:
Different compression quality levels and encoding parameters are applied to different regions of the 360-degree video based on local characteristics. Regions with less visual importance or lower spatial/temporal complexity receive higher compression, while critical regions maintain higher quality, optimizing the overall compression efficiency.
2Ease of manufacture
If image boundaries are divided using fixed predetermined locations, then the processing is simple, but the compression efficiency is not optimal and may be worse than not dividing the image at all
Solution Approach 1:
The image division boundaries are made dynamic rather than fixed. The encoder analyzes the actual image content and automatically adjusts the boundary locations to align with natural edges, contours, or regions of interest in the video content, optimizing compression efficiency for each specific scene.
Solution Approach 2:
The boundary location parameters are changed based on content analysis. Instead of using predetermined fixed coordinates, the system varies the boundary positions according to the spatial and temporal characteristics of the actual video content being encoded.
Data Source
Figure 1a~1b
Figure 1c
Figure 2a~2d
AI summary
There are disclosed various methods,apparatuses and computer programs for processing video information.In an embodiment of the method for encoding video information an image having a first edge and a second edge is obtained and a location suitable for a division boundary for dividing the image into a first part and a second part is searched. The image is rearranged by exchanging the order of the first part and the second part to obtain a reconstructed original image; and an indication of a location of the division boundary is provided. In an embodiment of the method for decoding video information an image obtained from an original image is received. The image has a first edge and a second edge. Also information indicative of a location of a division boundary is received. The division boundary divides the image into a first part and a second part. The image is rearranged by exchanging the order of the first part and the second part to obtain a reconstructed original image.