Content-Aware Dynamic Image Framing for Video Object Visibility
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Solution Overview
Problem
Existing video applications lack content-aware framing techniques to optimize the composition and enhancement of video content for specific use cases, such as remote training and classroom sessions, limiting the effectiveness of object recognition and presentation.
Innovation Solution
A method and system that utilize image analysis techniques, including AI and deep learning, to recognize objects in input video streams, isolate and enhance them, and compose frames based on content-aware templates, applying modifications like magnification and enhancement to create optimized output frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional video framing is used, then the video stream is transmitted in its original form, but object visibility and focus are not optimized for specific use cases
Solution Approach 1:
The patent segments the video processing into distinct functional modules: object detection module that identifies objects in the video stream, isolation module that separates detected objects from the background, and composition module that creates customized output frames. This segmentation allows each module to specialize in specific tasks, improving object visibility while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces an intermediary processing system between the video source and the output that performs content-aware framing. This intermediary system includes image analysis techniques and object detection algorithms that act as mediators to identify, isolate, and enhance key objects, thereby improving object visibility without requiring changes to the original video capture or transmission infrastructure.
2Loss of information
If content-aware framing is implemented, then object recognition and presentation are optimized, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary object detection and classification on the video stream before final frame composition. By pre-identifying objects of interest and determining their significance, the system prepares processing results in advance, which reduces the time required for final frame assembly and minimizes overall processing time while maintaining content presentation effectiveness.
Solution Approach 2:
The patent dynamically changes processing parameters such as object detection sensitivity, isolation thresholds, and enhancement levels based on the detected content and use case requirements. This adaptive parameter adjustment optimizes processing efficiency by applying appropriate levels of analysis only when necessary, reducing computational overhead and processing time while maintaining effective content presentation.
3Adaptability or versatility
If multiple video streams are processed simultaneously, then comprehensive content coverage is achieved, but system complexity and resource requirements increase
Solution Approach 1:
The patent implements a universal content-aware framing system that can process multiple video streams simultaneously using the same core modules for object detection, isolation, and composition. The system is designed to be multi-functional, handling different video sources, formats, and use cases through a unified architecture, which achieves comprehensive content coverage while managing system complexity through reuse of proven components.
Data Source
AI summary
Embodiments of the present invention disclose techniques for outputting content aware video based on at least one a video application use case. The technique recognizes objects associated with the use case and performs enhancement of the objects based on content-aware rules and composes at least some of the objects in an output frame based on content-aware frame composition templates. Embodiments of the present invention also disclose systems for implementing the above techniques.