Real-Time Face Beautification via Cloud GPU Offloading
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Solution Overview
Problem
Existing smartphone apps for video sharing and conferencing often lack real-time face beautification features in video mode, with many designed for offline image processing and limited functionality.
Innovation Solution
A scalable real-time face beautification system utilizing a graphics processing unit (GPU) with a cloud-based solution for platforms without a GPU, achieving low power consumption by customizing virtual graphics devices on servers, which includes skin tone detection, facial landmark analysis, and application of filters like face brightening, whitening, and slimming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If face beautification features are added to video mode, then functionality is improved, but power consumption increases
Solution Approach 1:
The face beautification system is segmented into multiple independent modules including skin tone detection, facial landmark analysis, and filter application. Each module can be independently processed and optimized, allowing the system to perform complex beautification tasks while managing power consumption through selective activation of processing modules based on device capabilities
Solution Approach 2:
A cloud-based solution acts as an intermediary for devices without native GPU support. The mobile device captures video and transmits it to remote servers that perform the computationally intensive face beautification processing, then returns the processed video. This intermediary approach enables advanced features on low-power devices by offloading processing to remote powerful GPUs
2Productivity
If real-time processing at high definition is achieved, then processing speed is improved, but computational complexity increases
Solution Approach 1:
The computationally intensive tasks of real-time face beautification are extracted from the mobile device and relocated to cloud-based GPU servers. The mobile device retains only lightweight functions for video capture, transmission, and display, while the complex processing of skin tone detection, landmark analysis, and filter application is performed remotely, enabling HD real-time processing without burdening the mobile device's computational resources
Solution Approach 2:
The system dynamically adapts its processing architecture based on device capabilities. Devices with native GPU support process video locally, while devices without GPU support utilize the cloud-based solution. This dynamic approach allows the system to maintain real-time HD processing performance across different device types by flexibly allocating computational tasks between local and remote resources
Data Source
AI summary
Systems, apparatus, articles of manufacture and methods for face augmentation in video are disclosed. An example apparatus includes executable code to detect a face of a subject in the video, detect a gender of the subject based on the face, detect a skin tone of the subject based on the face, apply a first process to smooth skin on the face in the video, apply a second process to change the skin tone of the face, apply a third process to slim the face, apply a fourth process to adjust a size of eyes on the face, and apply a fifth process to remove an eye bag from the face. One or more of the first process, the second process, the third process, the fourth process, or the fifth process adjustable based on one or more of the gender or an age. The example apparatus also includes one or more processors to generate modified video with beauty effects, the beauty effects based on one or more of the first process, the second process, the third process, the fourth process, or the fifth process.