Face Detection via Feature Prediction Model for Angle Adaptation
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Solution Overview
Problem
Existing face recognition technologies in intelligent devices suffer from low accuracy when the user's face is not directly facing the camera, leading to potential misrecognition and privacy leaks, as well as failure to activate intended functions like Auto Wake Up.
Innovation Solution
A method for human face detection that captures and analyzes facial features and outer contours using a feature prediction model trained with images from various angles, allowing for accurate detection regardless of the user's orientation relative to the camera.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional face recognition technology is used, then the system is simple to implement, but the detection accuracy drops drastically when the face is not facing the camera directly
Solution Approach 1:
The patent applies preliminary action by pre-training a feature prediction model with face images captured from multiple angles before actual face detection. The model is trained offline with labeled face feature information from various angles, so that when a face is detected, the system can predict the face angle and adjust recognition parameters in advance, thereby maintaining high accuracy without adding real-time complexity
Solution Approach 2:
The patent changes parameters by using a feature prediction model that predicts face angle information based on detected face features. The system adjusts recognition parameters dynamically based on the predicted angle, transforming the fixed-parameter traditional approach into a variable-parameter adaptive approach that maintains accuracy across different face orientations
2Adaptability or versatility
If face recognition is performed with angle variations, then the system becomes more versatile, but the recognition accuracy decreases due to insufficient training data
Solution Approach 1:
The patent applies universality by creating a feature prediction model that handles multiple face angles and orientations within a single unified system. The model is trained with diverse angle data and can predict various face orientations, making the system universally applicable to different face positions without requiring separate recognition algorithms for each angle
Solution Approach 2:
The patent implements feedback by using the predicted face angle information to adjust the recognition process. The feature prediction model outputs angle predictions that feed back into the recognition system, allowing the system to adapt its parameters based on the predicted orientation, thereby maintaining accuracy across different angles through iterative refinement
Data Source
AI summary
A human face detection method, falling within the technical field of image detection. The method comprises: respectively determining a plurality of pieces of human face characteristic information in a plurality of pre-input human face training samples, and training and forming a characteristic prediction model according to all the pieces of human face characteristic information in each of the human face training samples. The method further comprises: step S1, using an image acquisition apparatus to acquire an image; step S2, using a human face detector trained and formed in advance to determine whether the image comprises a human face, and if not, returning back to step S1; step S3, using a characteristic prediction model to obtain a plurality of pieces of human face characteristic information through prediction from the human face in the image; and step S4, constituting a facial structure associated with the human face according to the plurality of pieces of human face characteristic information obtained through prediction, and subsequently quitting. The beneficial effects of the technical solution are: being able to detect information about a human face comprising parts, such as the five sense organs and an outer profile, and improving the accuracy of human face detection.