Face Recognition Video Chat Power Reduction
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Solution Overview
Problem
Existing mobile terminals face high power consumption and expensive data transmission issues during video calls due to continuous camera operation and high data requirements, limiting their usage and battery life.
Innovation Solution
A user interface system that employs face recognition to analyze emotional characteristics in captured images, generating emotion indicative images only when there is a change, reducing unnecessary data transmission and power consumption by activating the camera module selectively based on events like message composition or emotional state changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the camera module operates continuously to capture images for video call, then real-time image transmission is achieved, but power consumption increases substantially
Solution Approach 1:
The camera module operates periodically rather than continuously, capturing images at specific intervals or triggered by detected emotional changes. This periodic operation maintains real-time communication capability while significantly reducing power consumption compared to continuous operation.
Solution Approach 2:
The patent extracts and transmits only the essential information (emotional characteristics from facial images) rather than continuous full-resolution images. By processing images locally and transmitting only relevant data, the system maintains real-time communication while reducing the energy burden of continuous image capture and transmission.
2Speed
If the camera module operates continuously to capture images for video call, then real-time communication is maintained, but battery lifetime is shortened
Solution Approach 1:
The camera module operates periodically rather than continuously, capturing images at specific intervals or triggered by detected emotional changes. This periodic operation maintains real-time communication capability while significantly reducing power consumption compared to continuous operation.
Solution Approach 2:
The patent extracts and transmits only the essential information (emotional characteristics from facial images) rather than continuous full-resolution images. By processing images locally and transmitting only relevant data, the system maintains real-time communication while reducing the energy burden of continuous image capture and transmission.
3Measurement precision
If full-resolution images are transmitted during video call, then image quality is maintained, but data transmission cost increases
Solution Approach 1:
The patent extracts only the essential emotional characteristics from facial images and transmits this extracted information instead of full-resolution images. This extraction approach maintains the functional quality needed for communication (emotional expression) while dramatically reducing data transmission volume and associated costs.
Solution Approach 2:
Instead of transmitting original full-resolution images, the system creates and transmits a simplified representation (emotional characteristic data) that captures the essential information. This copying approach preserves communication quality while reducing data transmission requirements.
4Speed
If facial image data is analyzed continuously to identify emotional characteristics, then real-time emotion detection is achieved, but processing power and energy consumption increase
Solution Approach 1:
The system extracts only the relevant emotional characteristics from facial images through local processing, rather than continuously analyzing and transmitting all image data. This extraction approach achieves real-time emotion detection while minimizing processing energy requirements.
Solution Approach 2:
The mobile terminal performs local image processing and emotional characteristic extraction using its own computational resources, eliminating the need for energy-intensive continuous transmission of raw image data to remote servers for analysis.
Data Source
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AI summary
A mobile device user interface method activates a camera module to support a video chat function and acquires an image of a target object using the camera module. In response to detecting a face in the captured image, the facial image data is analyzed to identify an emotional characteristic of the face by identifying a facial feature and comparing the identified feature with a predetermined feature associated with an emotion. The identified emotional characteristic is compared with a corresponding emotional characteristic of previously acquired facial image data of the target object. In response to the comparison, an emotion indicative image is generated and the generated emotion indicative image is transmitted to a destination terminal used in the video chat.