Camera Parameter Adjustment Using Depth Map Scene Classification
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Solution Overview
Problem
Current imaging devices lack an efficient method to automatically set parameters such as zoom, aperture, and shutter speed based on the scene, leading to suboptimal image capture.
Innovation Solution
The use of a depth map generated through various methods, including single-lens cameras and range sensors, to classify scenes and automatically adjust camera settings, such as zoom, aperture, and shutter speed, by computing histograms and detecting peaks to determine foreground and background thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual parameter setting is used, then the user has control over camera settings, but the image quality is suboptimal due to lack of automatic optimization
Solution Approach 1:
The camera system performs automatic parameter setting by itself using depth map analysis and scene classification algorithms. The device analyzes the captured image, generates a depth map, classifies the scene type, and automatically adjusts zoom, aperture, and shutter speed parameters without requiring user intervention, thereby achieving optimal image quality through self-service automation
Solution Approach 2:
The system dynamically changes camera parameters (zoom level, aperture size, shutter speed) based on the classified scene type. Different scene classifications trigger different parameter sets to optimize image quality for specific scenarios such as landscapes, portraits, or low-light conditions
2Manufacturing precision
If depth map is used for automatic parameter setting, then image quality is improved, but the device complexity increases
Solution Approach 1:
The depth map serves as an intermediary data structure that bridges the captured image and the parameter setting decision. Instead of directly analyzing the full-color image for parameter setting, the system first generates a simplified depth map that represents spatial information, which then guides the scene classification and parameter selection process
Solution Approach 2:
The parameter setting process is segmented into distinct modules: depth map generation, scene classification based on depth histogram analysis, and parameter adjustment. This segmentation allows each module to be optimized independently and facilitates systematic debugging and improvement of the overall system
3Adaptability or versatility
If scene classification is performed to determine parameter settings, then the adaptability to different scenes is improved, but the processing time increases
Solution Approach 1:
The system extracts only the essential depth information needed for scene classification by generating a depth map and computing its histogram, rather than analyzing all pixel data in the full-resolution image. This extraction of critical features (depth distribution statistics) enables fast scene classification while maintaining adaptability to different scene types
Solution Approach 2:
The depth map is generated and scene classification is performed before the final parameter setting and image capture. This preliminary analysis allows the system to pre-determine the optimal parameters based on scene type, so that when the actual photo is taken, the parameters are already optimized and ready, reducing overall processing time
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables automatic and optimal camera parameter settings, enhancing image composition by adjusting zoom, aperture, and shutter speed based on scene classification, resulting in improved image quality.
Implementation Method 1
receiving a first image signal with a first blur quantity at an image sensor after the first image signal passes through a lens at a first position, receiving one or more second image signals with a second blur quantity at the image sensor after the one or more second image signals pass through the lens at a second position
Data Source
AI summary
A Depth Map (DM) is able to be utilized for many parameter settings involving cameras, camcorders and other devices. Setting parameters on the imaging device includes zoom setting, aperture setting and shutter speed setting.