Dynamic Content Synthesis for Face Recognition Cameras
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing face recognition technologies do not effectively provide dynamic and personalized content synthesis based on facial features in camera images, limiting user engagement and diversity in applications such as animations and games.
Innovation Solution
A computer-implemented dynamic content providing system recognizes facial regions in images, extracts feature information by calculating face ratio data, and dynamically synthesizes content objects that match the facial features, allowing for personalized and varied synthesis results, including recommending content that aligns with the detected facial characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If face recognition technology is used to extract facial features, then personalized content synthesis can be achieved, but the system complexity increases due to multiple processing steps including face ratio calculation and feature extraction
Solution Approach 1:
The system segments the facial recognition process into distinct modules: face region detection, face ratio calculation, feature extraction, and content synthesis. Each module handles a specific task, making the overall complex system manageable and maintainable while achieving personalized content synthesis.
Solution Approach 2:
The patent introduces intermediate processing steps including face ratio calculation as a mediator between raw face detection and final feature extraction. This intermediary layer standardizes facial data before synthesis, enabling personalized content while maintaining systematic organization.
2Productivity
If dynamic content synthesis is performed based on facial features, then user engagement and diversity increase, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary face ratio calculation and feature extraction before actual content synthesis. By pre-processing facial data and storing extracted features, the system reduces processing time during content generation while maintaining diversity and personalization.
Solution Approach 2:
The patent changes processing parameters by calculating face ratios and extracting key features rather than processing entire facial images. This parameter transformation reduces computational complexity and processing time while preserving essential facial characteristics for personalized synthesis.
3Adaptability or versatility
If multiple facial regions are recognized and processed, then more comprehensive personalized content can be provided, but the complexity of feature extraction and synthesis increases
Solution Approach 1:
When multiple facial regions are detected, the system segments processing for each region independently, calculating face ratios and extracting features for each detected face. This segmentation approach handles multiple subjects without exponentially increasing complexity.
Solution Approach 2:
The patent implements a universal feature extraction process that works for both single and multiple facial regions. The same face ratio calculation and feature extraction algorithms are applied universally to each detected face, simplifying multi-face processing while achieving comprehensive personalization.
Data Source
AI summary
A dynamic content providing method performed by a computer-implemented dynamic content providing system including recognizing a facial region in an input image, extracting feature information of the recognized facial region, and dynamically synthesizing an image object of content based on the feature information, the content being synthesizable with the input image may be provided.