Video Encoding Segmentation for Bandwidth Reduction
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Solution Overview
Problem
Existing video surveillance methods consume significant network bandwidth due to the transmission of large quantities or sizes of moving objects in video images, despite using traditional encoding methods.
Innovation Solution
A video encoding method that separates and compresses background images while structuring foreground moving objects into metadata, reducing data transmission by encoding background images and transmitting only the compressed data along with the semantic metadata of foreground objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional video encoding methods are used to encode all video data, then video quality is maintained, but network bandwidth consumption increases significantly when moving objects are large in quantity or size
Solution Approach 1:
The patent segments the video content into background and foreground (moving objects) components. The background is encoded using traditional video encoding methods while the foreground objects are extracted and encoded separately with higher priority and quality. This segmentation allows differential treatment of different video components to optimize bandwidth usage.
Solution Approach 2:
The patent extracts moving objects from the background video frames and processes them separately. By taking out the foreground objects, the system can apply specialized encoding strategies to these critical elements while reducing the overall data volume that requires transmission, thereby lowering network bandwidth consumption.
2Reliability
If video data is transmitted without compression, then video quality is preserved, but storage space and network bandwidth requirements increase
Solution Approach 1:
The patent applies different quality levels and encoding strategies to different parts of the video content. Background areas receive standard compression while foreground moving objects are preserved with higher quality and priority. This local quality differentiation ensures that critical visual information is maintained while reducing overall data volume for transmission and storage.
Solution Approach 2:
The patent changes encoding parameters dynamically based on content importance. Moving objects are assigned higher priority encoding parameters, higher frame rates, and better quality settings compared to the background. This parameter differentiation optimizes the balance between video quality and resource consumption.
Data Source
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AI summary
The present application provides a video encoding method, decoding method and devices thereof. The video encoding device includes a video capturing unit for capturing a video image; a processing unit for performing compression encoding on a background image in the video image to obtain video compression data and for structuralizing a foreground moving object in the video image to obtain foreground object metadata; a data transmission unit for transmitting the video compression data and the foreground object metadata, wherein the foreground object metadata is data that stores video structuralized semantic information. In the case that the moving objects are large in quantity or in size, the amount of video data can be effectively reduced and the limitation of network bandwidth during transmission can be mitigated.