Video Recording System Sub-Area Motion Detection
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Solution Overview
Problem
Existing video recording methods in monitoring systems record unnecessary video frames, leading to wasted storage space and network bandwidth, as well as inefficiencies in retrieving key information due to the recording of irrelevant movements.
Innovation Solution
A video recording method that extracts images at predetermined intervals, performs region detection using a pre-established model to identify areas of interest, filters for motion events, divides areas into sub-areas, and compares image blocks to determine if a motion event has occurred, triggering recording only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous image recording is performed to ensure uninterrupted monitoring, then monitoring completeness is improved, but storage space and network bandwidth are wasted due to static video frames
Solution Approach 1:
The monitoring area is divided into multiple sub-areas, and the video stream is segmented into key frames and intermediate frames. Only key frames are stored and transmitted, while intermediate frames are discarded. This segmentation reduces the quantity of stored data while maintaining monitoring reliability through the key frame extraction mechanism.
Solution Approach 2:
The patent extracts only the essential key frames from the continuous video stream for storage and transmission. By taking out only the necessary frames (key frames) and discarding redundant intermediate frames, the system reduces storage space requirements while preserving the ability to retrieve key information when needed.
2Quantity of substance
If motion detection is used to trigger recording only when movement occurs, then storage space is saved, but irrelevant movements trigger false recordings
Solution Approach 1:
The patent applies local quality analysis by examining motion characteristics within specific sub-areas. Instead of triggering recording based on overall motion detection, the system analyzes motion patterns locally within divided sub-areas, comparing them against predetermined thresholds to distinguish between relevant and irrelevant movements, thereby improving recording accuracy.
Solution Approach 2:
The system performs partial motion analysis by dividing the monitoring area into sub-areas and applying motion detection only where necessary. By using a predetermined threshold for motion detection in each sub-area, the system avoids excessive false triggers while maintaining sufficient sensitivity to detect actual relevant movements.
3Loss of information
If all static video frames are stored to ensure complete record, then information completeness is improved, but retrieval efficiency deteriorates due to searching through long time spans
Solution Approach 1:
The patent extracts only key frames from the continuous video stream for storage. By taking out only the essential frames that contain significant information, the system reduces the amount of data that needs to be searched through during retrieval operations, thereby improving retrieval efficiency while maintaining information completeness for key events.
Solution Approach 2:
The system performs preliminary action by pre-dividing the monitoring area into sub-areas and pre-establishing motion detection thresholds. This preliminary preparation enables faster retrieval operations, as the system already has the structural framework in place to quickly identify and access relevant key frames without having to search through all stored frames sequentially.
Data Source
AI summary
A video recording method is disclosed including: extracting every predetermined time period a first image captured by a monitoring camera; performing region detection on the first image to extract areas of interest covering some or all parts of a target object; performing motion area filtering on the areas of interest to select one or more target areas; dividing each target area into multiple sub-areas; extracting every predetermined time period a second image captured by the monitoring camera; comparing an image block located in each sub-area of the second image with that in the same sub-area of the second image previously extracted, to determine whether a motion event has occurred in each sub-area; and controlling the monitoring camera to start video recording from the currently extracted second image when a motion event has occurred in a sub-area. A server, system, and storage medium suitable for the method are also disclosed.