Video Cropping Preserving Regions of Interest
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing videoconferencing systems often crop regions of interest close to the image edges, leading to the loss of relevant information during video conferencing, as they lack effective methods to maintain these regions within the displayed image.
Innovation Solution
The system employs automatic and semi-automatic methods to define and maintain regions of interest by using motion detectors, flesh tone analysis, and far-end camera control signals to adjust camera settings, ensuring that regions of interest are kept within the cropped image area, and provides visual and audio cues to users to adjust their camera settings accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the video image is cropped by the MCU to fit within an allocated area, then the video image fits the display area, but regions of interest close to the edges may be cropped out
Solution Approach 1:
The system performs preliminary action by detecting the region of interest in advance before cropping occurs. The MCU analyzes the video image to identify important regions (such as faces or speakers) and uses this information to determine crop boundaries that preserve these regions, preventing them from being cut off at the edges.
Solution Approach 2:
The system implements feedback by continuously monitoring the video image content and adjusting the crop area accordingly. The MCU receives feedback about the position and size of regions of interest and dynamically modifies the cropping parameters to ensure these regions remain within the displayed area while still fitting the allocated display space.
2Extent of automation
If automatic methods are used to define regions of interest, then the system can automatically maintain important areas, but the complexity of the system increases
Solution Approach 1:
The system applies self-service by enabling the video conferencing system to automatically define and maintain regions of interest without requiring external intervention. The MCU autonomously analyzes video content, identifies important regions using algorithms (such as face detection or motion detection), and adjusts cropping parameters automatically, making the system self-sufficient in preserving critical visual information.
Data Source
AI summary
Systems and methods are disclosed for controlling cropping areas of video images to match the allocated area associated with the image in a video conferencing layout. The disclosed methods can protect regions of interest from being cropped. A region of interest within a video image is identified to adjust the cropping in such a way that the region of interest is preserved within the cropped image. The region of interest may be identified based on motion detection or flesh tone detection, for example.