Rotation-Adaptive Surveillance Camera for Vertical FOV Analytics
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Solution Overview
Problem
Surveillance cameras typically capture video frames with a wider horizontal dimension than vertical, wasting FOV and making it difficult to monitor scenes like corridors or roads, and rotating them post-capture does not allow for proper video analytics due to mismatched aspect ratios.
Innovation Solution
A surveillance camera system that includes an imaging sensor, an adjustable mount for rotation, and a logic device to determine and adapt the video frames' orientation, generating frames with a vertical dimension corresponding to the camera's rotational orientation, enabling native rotation-adaptive video analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the camera is mounted on its side to capture more vertical area, then the vertical FOV is improved, but the video image frames become difficult to interpret and analytics become difficult
Solution Approach 1:
The system performs preliminary rotation of the captured image to the correct orientation before any analytics or interpretation occurs. The processor automatically rotates the captured image based on the detected camera orientation, so that subsequent analytics operations can proceed with properly oriented images without requiring manual intervention or complex post-processing.
Solution Approach 2:
The system introduces an intermediary rotation transformation layer between the camera capture and the analytics processing. This intermediary step takes the raw captured image, applies the appropriate rotation based on camera orientation, and produces a corrected image that maintains the intended FOV while being suitable for analytics operations.
2Productivity
If the camera maintains its standard horizontal FOV orientation, then video analytics can be performed, but the vertical dimension is insufficient for monitoring long corridors or roads
Solution Approach 1:
The system dynamically adapts the FOV orientation based on the camera's physical mounting orientation. Rather than being fixed to a horizontal aspect ratio, the system can rotate the captured image to match the camera's actual field of view, allowing the same camera hardware to serve multiple surveillance scenarios (corridor monitoring, road monitoring, etc.) without requiring physical reconfiguration.
3Area of stationary object
If post-capture rotation is applied to match desired FOV, then the FOV orientation is improved, but video analytics cannot be performed due to aspect ratio mismatch
Solution Approach 1:
The system performs the rotation operation as a preliminary action during the capture process rather than as a post-processing step. By determining the camera orientation at the time of capture and applying the corresponding rotation immediately, the system ensures that the resulting image is already in the correct orientation for analytics operations, eliminating the aspect ratio mismatch problem.
Data Source
AI summary
Various embodiments of the methods and systems disclosed herein may be used to provide a surveillance camera that generates native video image frames in the appropriate FOV (orientation) that corresponds to the orientation in which the surveillance camera is installed when the video image frames are captured. The surveillance cameras implemented in accordance with embodiments of the disclosure may facilitate installation that provides a desired FOV in a particular orientation, generate video image frames that natively correspond to the desired FOV, and allow user interaction and video analytics to be performed on the FOV-matched video image frames.