Real-Time Face Detection in User Equipment Media
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Solution Overview
Problem
Current user equipment (UE) systems do not effectively leverage facial recognition for real-time media playback, missing opportunities for enhancing user interactions and media management.
Innovation Solution
Implementing facial recognition on UE to identify prevalent faces in stored media files and apply actions such as adding enhancement effects or authorizing operations based on the presence of these faces in real-time media streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If facial recognition is implemented to detect faces in stored media files and apply actions in real-time media, then user experience and media management functionality are enhanced, but device complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary facial recognition on stored media files to build a database of prevalent faces before real-time processing. This pre-processing step allows the system to quickly compare real-time media against the pre-analyzed face database, reducing the complexity of real-time operations while maintaining enhanced media management functionality.
Solution Approach 2:
The system automatically identifies prevalent faces and applies enhancement effects without requiring manual user configuration. The facial recognition system self-manages the process of detecting faces, determining prevalence, and applying appropriate actions, thereby enhancing functionality while minimizing the operational complexity for users.
2Ease of operation
If facial recognition scanning is performed on real-time media streams, then interactive features and media enhancement are improved, but processing time and computational resources increase
Solution Approach 1:
The system applies facial recognition processing selectively rather than uniformly across all real-time media. It focuses computational resources on detecting prevalent faces that have been identified from stored media, applying enhancement effects only where relevant. This localized approach improves interactive features while reducing overall processing time and resource consumption.
3Adaptability or versatility
If multiple actions are applied based on prevalent face detection, then user experience is enhanced, but system resource consumption increases
Solution Approach 1:
The system applies a subset of available actions based on the specific context and detected prevalent faces rather than applying all possible enhancements uniformly. It selects and applies only the most relevant actions for each situation, thereby enhancing user experience in a targeted manner while reducing overall energy consumption compared to applying all actions in all cases.
Data Source
AI summary
In an embodiment, a user equipment (UE) recognizes a set of faces within a set of media files stored on the UE using facial recognition. The UE identifies a set of prevalent faces based on a set of criteria including a prevalence of one or more faces among the set of media files. The UE scans real-time media using facial recognition to determine whether any prevalent faces from the set of prevalent faces are present in the real-time media. The UE performs an action based on whether the scanning detects any prevalent faces from the set of prevalent faces in the real-time media. By way of example, the action may include adding one or more enhancement effects to the real-time media, authorizing a communicative operation to proceed, authorizing access to the UE, or any combination thereof.