Face Detection and Recognition System for Digital Image Classification
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Solution Overview
Problem
Current technologies lack efficient methods for automating the classification and organization of consumer digital images, particularly in managing collections that are constantly growing, and fail to utilize face recognition for image management and access.
Innovation Solution
A processor-based system with embedded programming instructions for automated face detection and recognition, which classifies and archives images by identifying face regions, normalizing them, extracting face classifier parameter values, and comparing these to a database of known identities for grouping and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated face detection and recognition is implemented, then productivity of image classification is improved, but device complexity increases
Solution Approach 1:
The system divides the image classification task into distinct modules: face detection module, face recognition module, and classification module. Each module handles a specific aspect of the processing pipeline, allowing for specialized optimization while maintaining overall system productivity.
Solution Approach 2:
The patent introduces intermediate data structures and processing layers between face detection and final classification. Face features are extracted and stored as intermediate representations that can be reused across multiple classification queries, reducing redundant computations.
2Manufacturing precision
If database-wide sorting and grouping operations are performed frequently, then image organization quality is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary face detection and feature extraction when images are first added to the database, preparing data in advance for future classification operations. This preliminary processing reduces the computational burden during subsequent sorting and grouping operations.
Solution Approach 2:
Instead of performing database-wide sorting operations continuously, the system implements periodic batch processing that reorganizes images at scheduled intervals or when triggered by specific events, reducing overall processing time while maintaining organization quality.
3Adaptability or versatility
If manual image categorization is required, then adaptability to user needs is improved, but loss of time increases
Solution Approach 1:
The system automatically performs face detection, recognition, and image categorization without requiring user intervention. The automated classification adapts to user preferences through configurable parameters and learning from user corrections, eliminating manual categorization time while maintaining adaptability.
Solution Approach 2:
The system incorporates feedback mechanisms where user corrections and preferences are used to refine and improve automated classification accuracy over time. This allows the system to become increasingly adaptive to specific user needs while maintaining automation.
Data Source
AI summary
A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region. A face recognition module extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. A database module serves to archive data corresponding to the new faceprint and its associated parent image according to the associating by the workflow module within one or more digital data storage media. A set of user interface modules serve to obtain user input in the classifying of faceprints and their associated normalized face regions and parent images.