Scheduled Video Region Extraction for Bandwidth Optimization
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Solution Overview
Problem
Current practices in video surveillance involve transmitting the entire high-resolution field of view from cameras, which is resource-intensive and inefficient, as a large portion of the frame may not be of interest to consumers, leading to unnecessary data transfer and processing.
Innovation Solution
A system and method for selecting and preprocessing a region of interest from streaming video data, using a runtime configuration file to define preprocessing parameters such as cropping, formatting, and image processing techniques, allowing for real-time adjustments based on factors like time of day, and switching camera sources if necessary, to create a subset of the video data that is more suitable for downstream processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the entirety of high-resolution streaming video data is transmitted to consumers, then complete visual information is provided, but data transfer and processing resources are excessively consumed
Solution Approach 1:
The patent extracts only the region of interest (ROI) from the complete video frame and transmits it to consumers. The gateway identifies and extracts the ROI based on preprocessing parameters, discarding irrelevant portions of the frame. This extraction principle directly resolves the contradiction by providing necessary visual information while eliminating unnecessary data transfer.
Solution Approach 2:
The patent applies different quality and processing levels to different regions of the video frame. The ROI receives full processing and transmission quality, while non-ROI areas are either heavily downsampled or completely discarded. This local quality differentiation allows the system to optimize resource usage while maintaining information quality where needed.
2Adaptability or versatility
If preprocessing parameters are changed to adapt to different conditions (e.g., time of day, lighting), then video quality is optimized for specific use cases, but system complexity increases
Solution Approach 1:
The patent implements dynamic preprocessing parameters that automatically adjust based on environmental conditions such as time of day and lighting levels. The gateway dynamically switches between different preprocessing configurations (e.g., daytime vs. nighttime modes) without requiring manual intervention. This dynamic adaptation resolves the contradiction by providing condition-optimized video quality while automating the complexity management.
Solution Approach 2:
The patent changes key preprocessing parameters (such as brightness adjustment, contrast enhancement, and ROI selection criteria) based on detected environmental conditions. For example, nighttime mode applies different brightness and contrast parameters compared to daytime mode. This parameter adaptation allows the system to optimize video quality for different conditions while using a unified system architecture.
3Manufacturing precision
If multiple preprocessing operations are applied to video data, then video quality and suitability for downstream processing is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary preprocessing operations at the gateway before video data is transmitted to consumers or downstream processing systems. By pre-applying operations such as ROI extraction, formatting, and basic image processing, the system ensures that video data arrives at the consumer already optimized and ready for immediate use. This preliminary action resolves the contradiction by improving video quality while reducing the processing burden on downstream systems.
Data Source
AI summary
A method of scheduled modifications of preprocessing of incoming video data of at least one region of interest from a camera collecting video data having a first field of view includes receiving incoming video data from the camera and preprocessing the incoming video data, by a computer processor, according to preprocessing parameters defined within a runtime configuration file. The preprocessing includes formatting the incoming video data to create first video data of a first region of interest with a second field of view that is less than the first field of view. The method also include publishing the first video data of the first region of interest to an endpoint to allow access and processing by a subscriber; in response to a time schedule, altering the preprocessing parameters defined within the runtime configuration file dependent upon the time schedule to create second video data that is different from the first video data; and publishing the second video data to the endpoint to allow access and processing by the first subscriber.