Video Stream ROI Display via Segmented Encoding
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Solution Overview
Problem
Current video streaming technologies face challenges in efficiently displaying regions of interest (ROI) with higher quality without requiring excessive processing resources, especially when dealing with Ultra High Definition (UHD) videos, as transmitting full video streams is bandwidth-intensive and complex computations are needed for encoding and transcoding.
Innovation Solution
The method involves subdividing video streams into a grid of image portions, encoding some portions with higher resolution, and encapsulating them in a file with resolution level data, allowing for dynamic selection and display of high-resolution ROIs without necessitating complex data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the full video stream is transmitted with high quality, then the display quality of the entire video is improved, but the bandwidth requirement increases significantly
Solution Approach 1:
The video stream is divided into multiple encoded video streams, each containing different image portions (tiles) encoded at different resolutions. This segmentation allows selective transmission of only the high-resolution regions of interest rather than the entire video stream, thereby maintaining high display quality for important areas while significantly reducing overall bandwidth consumption.
Solution Approach 2:
Different portions of the video are encoded with different quality levels. Specifically, certain image portions corresponding to regions of interest are encoded at high resolution, while other portions are encoded at lower resolution. This local quality differentiation ensures that bandwidth is allocated efficiently to areas that matter most to the user, improving perceived quality without proportionally increasing bandwidth requirements.
2Manufacturing precision
If the video stream is encoded with high quality from the beginning, then the display quality is improved, but the processing complexity and computational resources required increase
Solution Approach 1:
The video stream is pre-encoded into multiple encoded video streams with different image portions at different resolutions before transmission. This preliminary action creates a structured format where high-resolution regions are already prepared and identified, eliminating the need for complex real-time processing or transcoding operations at the receiving end when regions of interest are determined.
Solution Approach 2:
The system allows dynamic selection of regions of interest after the video has been encoded. Users can dynamically determine which areas to view in high quality, and the pre-encoded structure enables flexible extraction and display of these regions without requiring re-encoding or complex computational operations, thus reducing processing complexity while maintaining quality flexibility.
3Manufacturing precision
If the ROI is determined in advance and the video is transcoded accordingly, then the display quality of the ROI is improved, but the processing time and computational resources increase
Solution Approach 1:
Multiple encoded video streams are prepared in advance with different image portions encoded at different resolutions. This preliminary encoding creates a ready-to-use structure where high-resolution ROI data is already available in the transmitted stream, eliminating the need for time-consuming transcoding operations after the ROI is identified by the user.
Solution Approach 2:
Instead of transcoding the entire video stream when ROI is determined, the system extracts and uses the pre-encoded high-resolution portions from the appropriate encoded video streams. This copying approach retrieves the needed high-quality data directly from the prepared streams without requiring additional encoding or transcoding processing, thus avoiding time loss while maintaining ROI quality.
4Manufacturing precision
If complex transcoding operations are performed to extract and re-encode the ROI, then the display quality of the ROI is improved, but the processing resources required increase
Solution Approach 1:
The video is segmented into multiple encoded streams with different spatial resolutions for different image portions. This segmentation allows the receiver to directly extract the high-resolution ROI portions from the appropriate stream without performing complex transcoding operations, thereby reducing the processing resources and power consumption required while maintaining high display quality for the region of interest.
Solution Approach 2:
The system extracts pre-encoded high-resolution ROI data from the transmitted encoded video streams and uses it directly for display. This copying approach avoids the need for resource-intensive transcoding operations, as the high-quality data is already prepared in the transmitted streams, thus minimizing processing resource requirements while achieving the desired ROI display quality.
Data Source
AI summary
A method of processing video data comprising subdividing a video stream into image portions, encoding the image portions with high resolution in respective encoded video streams and reassembling a selection of encoded video streams in order to display a region of interest with high resolution. Embodiments of the invention provide high resolution display of specific region of interest without a priori knowledge of the position of the region of interest.