Camera Exposure Switching for Rapid Indoor Lighting Changes
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Solution Overview
Problem
Conventional exposure algorithms in surveillance cameras struggle to adapt quickly to rapidly changing indoor lighting conditions, leading to over- or under-exposed images and difficulties in distinguishing objects, especially when light sources are switched on or off.
Innovation Solution
A method involving determining first and second camera settings for different lighting conditions, obtaining a reference image under one setting, and comparing image feature data to rapidly detect changes, allowing direct switching between settings without iterative adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional automatic exposure algorithms are used to control camera settings, then the camera can adapt to slowly changing outdoor lighting conditions, but it cannot adapt quickly enough to rapidly changing indoor lighting conditions, resulting in over- or under-exposed images
Solution Approach 1:
The system pre-determines multiple camera settings corresponding to different lighting conditions (e.g., dark, normal, bright) before actual use. When a lighting change is detected through image feature comparison, the camera directly switches to the pre-determined appropriate setting rather than gradually adjusting, enabling immediate adaptation and eliminating exposure quality loss during transitions.
2Productivity
If the camera uses iterative incremental adjustments to adapt to lighting changes, then it can maintain stable settings, but it takes significant time to adapt, causing valuable monitoring moments to be lost
Solution Approach 1:
Multiple camera settings for different lighting conditions are predetermined and stored in advance. Upon detecting a lighting change through reference image comparison, the system directly switches to the appropriate pre-determined setting, bypassing iterative adjustments entirely. This enables immediate adaptation and ensures continuous high-quality monitoring without time loss.
Solution Approach 2:
The system continuously compares current image feature data with reference image feature data to detect lighting changes. This feedback mechanism triggers immediate switching between pre-determined camera settings, ensuring the camera responds rapidly to lighting variations and maintains optimal monitoring effectiveness without iterative delays.
3Reliability
If the camera rapidly switches settings to adapt to lighting changes, then it can maintain proper exposure, but it requires complex algorithms to detect and respond to lighting changes quickly
Solution Approach 1:
The system uses reference images captured under known lighting conditions as an intermediary to detect and classify current lighting conditions. By comparing current image feature data with reference image feature data, the system can quickly identify the appropriate lighting category (dark, normal, bright) and switch to the corresponding pre-determined camera setting, simplifying the detection algorithm while maintaining rapid response and exposure consistency.
Data Source
AI summary
Controlling a camera includes determining a first camera setting for monitoring a scene under a first lighting condition, and a second camera setting for monitoring the scene under a second lighting condition. The method further includes obtaining a reference image that represents the scene under the second lighting condition, as captured in the first camera setting. While monitoring the scene in the first camera setting, detecting a change in the scene from the first to the second lighting condition. The detecting the change includes performing a comparison between first image feature data derived from a first image of the scene captured with the camera set to the first camera setting, after the change from the first to the second lighting condition, and reference image feature data derived from the reference image, to determine that the first image feature data matches the reference image feature data.