Face Recognition for Automatic Mobile Display Adjustment
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Solution Overview
Problem
Mobile phones cannot effectively determine the current usage conditions of users, such as distance and posture, leading to difficulties in adjusting content display for clear viewing.
Innovation Solution
A face recognition method that includes illumination estimation, wavelet transform, inverse wavelet transform, and histogram clipping processing to recognize the user's face and adjust the display settings, such as picture size and position, based on the detected face image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the mobile phone uses traditional touch screen or key input methods, then the user can adjust display content, but the user operation burden increases and the mobile phone cannot automatically acquire usage conditions
Solution Approach 1:
The mobile phone performs self-service by automatically capturing images of the user's face through the camera, processing these images to determine usage conditions (distance, posture), and adjusting display content without requiring any manual input from the user. The system serves itself by acquiring its own operational parameters through face recognition technology.
Solution Approach 2:
The patent replaces the mechanical input system (touch screen or physical keys) with an optical recognition system. Instead of requiring physical user interaction to adjust display, the system uses camera imaging and image processing algorithms to automatically detect usage conditions and make adjustments, substituting mechanical operation with optical-field detection and computational processing.
2Adaptability or versatility
If the mobile phone cannot detect usage conditions, then the device structure remains simple, but the display cannot be automatically adjusted for clear viewing
Solution Approach 1:
The patent makes the camera serve multiple functions: it is used both for its traditional purpose of capturing images and videos, and additionally for face recognition to determine usage conditions. By making the camera a multi-functional component, the system gains adaptability without adding dedicated specialized hardware, thus managing device complexity while improving display adaptation capability.
Solution Approach 2:
The system determines usage conditions by analyzing changes in face image parameters such as size, position, and illumination characteristics. By monitoring these parameter variations in the captured face images, the system infers usage conditions (distance, posture, lighting) and adjusts display parameters accordingly, enabling adaptability through software-based parameter analysis rather than hardware complexity.
3Ease of operation
If the user manually adjusts display content through touch screen or keys, then the display can be optimized for viewing, but the user experience is degraded due to additional operation steps
Solution Approach 1:
The system performs preliminary action by continuously or periodically capturing face images and determining usage conditions in advance, before the user needs to adjust the display. The mobile phone proactively analyzes the user's face position and distance, and automatically adjusts display content beforehand, eliminating the need for user intervention and reducing the time loss associated with manual adjustment.
Solution Approach 2:
The system implements a feedback loop where the camera continuously monitors the user's face, the image processing module analyzes usage conditions, and the display module adjusts content based on this feedback. This closed-loop system automatically optimizes display for viewing comfort, improving user experience by eliminating manual adjustment steps and reducing the time users spend on operational tasks.
Data Source
AI summary
Disclosed are a face recognition method and device, and a picture display method and device. The face recognition method includes: performing illumination estimation processing on an original face image to obtain a first face image (step 101); performing wavelet transform processing on the original face image to obtain a face image component (step 102); performing inverse wavelet transform processing on the face image component to obtain a second face image (step 103); performing histogram clipping processing on the second face image to obtain a third face image (step 104); and recognizing a face according to the first face image and the third face image (step 105). Through the above face recognition method and device, and the picture display method and device, the face can be recognized by the mobile phone and the user does not need to input an instruction via a touch screen or a key to adjust a displayed content. Therefore, the operation amount of the user is reduced, the intelligent degree of the mobile phone is improved, the convenience and the practicability for the user to use the mobile phone are enhanced and the user experience is improved.