Camera Parameter Adjustment Using Historical Scene Data
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Solution Overview
Problem
Mobile devices, such as smartphones and tablets, require manual adjustment of photography parameters like brightness, contrast, and exposure for different scenes, which can be inconvenient and time-consuming, and do not account for user preferences or habits.
Innovation Solution
A method that determines the current photographing scene using a convolutional neural network, acquires pre-stored historical adjustment information, calculates current adjustment information based on this data, and adjusts the preview image accordingly, allowing automatic parameter adjustment without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual adjustment of photography parameters is required for different scenes, then the device can accommodate various photography needs, but the operation becomes inconvenient and time-consuming
Solution Approach 1:
The system automatically adjusts photography parameters by analyzing historical adjustment information and current scene characteristics, enabling the device to serve itself without requiring manual user intervention for parameter adjustment in different photography scenes
Solution Approach 2:
The system pre-stores historical adjustment information from previous photography sessions and uses it to proactively determine optimal parameters before the user needs to adjust them, allowing the device to prepare adjustment settings in advance based on scene recognition
2Adaptability or versatility
If manual adjustment of photography parameters is required, then users can control each parameter, but the process does not account for user preferences or habits
Solution Approach 1:
The system incorporates user feedback by analyzing historical adjustment information from previous sessions to understand user preferences and habits, then uses this feedback to automatically determine optimal photography parameters that align with individual user behavior patterns
Solution Approach 2:
The system automatically adapts to user preferences by learning from historical data and making parameter adjustments autonomously, eliminating the need for users to manually control each parameter while still personalizing results to their specific preferences
3Productivity
If automatic scene recognition is implemented, then parameter adjustment becomes faster, but the system complexity increases
Solution Approach 1:
The system performs preliminary scene recognition and parameter determination automatically based on historical data, preparing adjustment settings in advance before the user needs them, which speeds up the overall process while using manageable computational resources
Solution Approach 2:
The system uses historical adjustment information as a template or copy from previous similar scenes, applying proven parameter settings to current scenes without requiring complex real-time analysis, thus maintaining simplicity while achieving fast adaptation
Data Source
AI summary
A photographing method and device, a storage medium and an electronic apparatus are disclosed. The method includes the following. A current photographing scene is determined based on a current preview image. Based on the current photographing scene, pre-stored historical adjustment information of a photographing parameter matching the current photographing scene is acquired. Current adjustment information is determined based on the historical adjustment information. Adjustment is performed on the current preview image on the basis of the current adjustment information, and an adjusted current preview image is output.