Dynamic Resolution Switching for Video Object Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
High-resolution video streams require significant computational resources for image analysis, leading to increased load on computing devices, especially in surveillance systems with multiple IP cameras, as they need to process and recognize objects efficiently, which can be hindered by the heavy computation required for decompressing and analyzing high-resolution frames.
Innovation Solution
An image analysis method and device that selectively loads video streams of varying resolutions, determining if an object exists in a frame and matches preset conditions, switching to a higher resolution stream if the object is not recognizable in the initial stream, thereby optimizing image analysis by adjusting resolution based on recognition needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution video streams are used for image analysis, then object recognition accuracy is improved, but computational load increases
Solution Approach 1:
The system dynamically changes the resolution parameter of video streams based on analysis needs. It starts with low-resolution streams for initial object detection, and only switches to high-resolution streams when detailed analysis is required, thus adjusting the parameter to balance accuracy and computational load
Solution Approach 2:
The video analysis process is segmented into multiple stages: initial object detection using low-resolution streams, and detailed analysis using high-resolution streams only when needed. This segmentation allows the system to process video data in stages, reducing overall computational burden while maintaining recognition accuracy
2Area of stationary object
If multiple high-resolution video streams are processed simultaneously, then surveillance coverage is improved, but processing time increases
Solution Approach 1:
The system changes the resolution parameter dynamically for different video streams and at different times. Multiple low-resolution streams are processed simultaneously for broad coverage, and high-resolution processing is applied selectively to specific streams or time periods when detailed analysis is needed
Solution Approach 2:
The system employs periodic switching between low-resolution and high-resolution processing modes. Low-resolution processing occurs continuously for all streams to maintain coverage, while high-resolution processing is applied periodically or on-demand to specific frames or regions requiring detailed analysis
Data Source
AI summary
A device, method for image analysis and a computer-readable medium are provided. The method includes loading a first video stream having a first resolution, and selecting one first video frame of the first video stream. When an object exists in the selected first video frame, determine whether an image of the object in the selected first video frame matches a preset condition. If yes, the method performs image analysis to the image of the object in the selected first video frame. If not, the method loads a second video stream having a second resolution higher than the first resolution, selects one second video frame of the second video stream that the object exists in it, and performs the image analysis to an image of the object in the selected second video frame.