Auto-Exposure Controller for Structured Light Depth Sensing
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Solution Overview
Problem
Existing auto exposure (AE) algorithms for depth sensing applications are inadequate in handling brightness changes, object depth variance, surface properties, noise, and motion blur, leading to poor decode quality.
Innovation Solution
An AE control method that adjusts multiple exposure parameters based on a decode rate value determined from a depth map and region of interest (ROI), using a scene change detection circuit to iteratively adjust parameters such as projector power, analog gain, and exposure time with a gradient descent method, with a step size determined by the decode rate and detection result.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single exposure parameter is used for AE adjustment, then the AE algorithm is simple to implement, but it cannot handle brightness changes, depth variance, surface properties, noise, and motion blur effectively, resulting in poor decode quality
Solution Approach 1:
The patent divides the image into multiple depth regions (near, mid, far) based on depth information, and applies different exposure parameters to each region. This segmentation allows the system to handle different depth zones with optimized exposure settings, improving decode quality for objects at various distances while maintaining manageable algorithm complexity through region-based processing.
Solution Approach 2:
The patent transitions from single-parameter exposure control to multi-parameter control by incorporating depth information as an additional dimension. The exposure adjustment is no longer based solely on overall image brightness but combines brightness with depth metrics, enabling differentiated exposure strategies for near, mid, and far regions simultaneously.
2Manufacturing precision
If multiple exposure parameters are adjusted simultaneously, then decode quality can be improved, but the adjustment process becomes complex and computationally intensive
Solution Approach 1:
The patent implements dynamic adjustment of exposure parameters based on real-time depth map analysis. The system adaptively determines near, mid, and far region boundaries and adjusts exposure parameters dynamically according to the actual scene depth distribution, allowing flexible optimization without fixed complex rule sets.
Solution Approach 2:
The patent changes physical parameters (exposure time, gain, projector power) based on depth-region analysis. By categorizing pixels into near/mid/far regions and applying parameter changes specific to each region, the system achieves sophisticated multi-parameter control while maintaining algorithmic simplicity through clear parameter-change rules for each depth zone.
3Adaptability or versatility
If exposure parameters are adjusted frequently to adapt to scene changes, then AE performance can be improved, but processing time and computational load increase
Solution Approach 1:
The patent implements periodic scene change detection by comparing current depth maps with reference depth maps at intervals. Instead of continuous monitoring, the system performs discrete comparisons to detect significant scene changes, triggering exposure parameter adjustments only when necessary. This periodic approach maintains adaptability while reducing unnecessary processing overhead.
Solution Approach 2:
The patent uses feedback from depth map analysis and scene change detection to trigger exposure parameter adjustments. The system continuously monitors depth information and compares it against reference data, using this feedback to determine when scene changes warrant parameter re-adjustment, thereby optimizing the balance between adaptability and processing efficiency.
Data Source
AI summary
An auto-exposure (AE) control system, includes a camera configured to capture an input image, a region of interest (ROI) determination circuit configured to determine a ROI of the input image, a depth decoder and an AE controller. The depth decoder is configured to generate a depth map of the input image and determine a decode rate value according to the depth map of the input image and the ROI of the input image. The AE controller includes an exposure adjustment circuit which is configured to receive a decode rate value and the detection result and sequentially adjust a plurality of the exposure parameters according to the variation of the decode rate value. A step size for adjusting the plurality of the exposure parameters is determined according to the variation of the decode rate value and the detection result.