Smart Video Rendering for Primary Object Resolution Preservation
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Solution Overview
Problem
Existing video sequence display technologies downscale high-resolution videos to lower resolutions, leading to loss of detail and a less engaging viewing experience, especially when displaying primary objects within a scene.
Innovation Solution
A method and apparatus that selectively focus on primary portions of image frames, maintaining or upscaling their resolution while discarding secondary portions, allowing for enhanced display of primary objects without downscaling, using control data to determine and highlight the positions and sizes of primary objects within the video sequence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video sequence is downscaled from high resolution to lower resolution for display, then display compatibility is improved, but image quality and detail are lost
Solution Approach 1:
The video sequence is divided into multiple portions with different resolutions. Primary portions containing important objects are maintained at high resolution, while secondary portions are downscaled. This segmentation allows different parts of the video to have different quality levels, preserving overall image quality while ensuring display compatibility.
Solution Approach 2:
Different portions of the video sequence are assigned different quality levels based on their importance. Primary portions containing key objects maintain high resolution and detail, while secondary portions use lower resolution. This local quality approach ensures that critical visual information is preserved while adapting to display constraints.
2Manufacturing precision
If entire video sequence is maintained at high resolution, then image quality is preserved, but data transmission and processing load increase
Solution Approach 1:
The video data is segmented into primary and secondary portions, allowing selective transmission of high-resolution data only for important regions. This reduces the total data volume compared to transmitting entire high-resolution video, while maintaining image quality where it matters most.
Solution Approach 2:
The essential visual information (primary portions containing important objects) is extracted and maintained at high resolution, while non-essential portions are reduced. This extraction approach preserves critical image quality while minimizing unnecessary data transmission.
3Device complexity
If traditional downsampling is applied to all pixels, then processing simplicity is maintained, but detail and clarity of important objects are lost
Solution Approach 1:
The video sequence is segmented into primary and secondary portions based on object importance. This segmentation enables differentiated processing where primary portions retain high resolution and secondary portions are downscaled, preserving object detail while maintaining processing feasibility through automated analysis.
Solution Approach 2:
The system performs preliminary analysis to identify primary portions containing important objects before the downscaling process. This preliminary action allows the system to make informed decisions about which regions to preserve at high resolution, ensuring object detail is maintained before any processing occurs.
Data Source
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AI summary
A method generating control data for displaying a video sequence on a low resolution display may comprise providing at least a first video sequence, the first video sequence comprising a plurality of image frames, determining whether a first image frame of the first video sequence comprises a sub-image of a primary object, selecting a first position of a primary image portion of an image frame such that the first position substantially matches with the position of the sub-image of the primary object, if the first image frame has been determined to comprise said sub-image of said primary object and providing control data, which indicates said first position.