Facial Critical Area Tracking via Coordinate Frame Transfer
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Solution Overview
Problem
Existing face tracking algorithms face challenges in achieving robust adaptation and real-time processing simultaneously due to increased complexity, leading to low tracking efficiency in video files or video streams, as they require extensive face detection and critical area positioning on each frame.
Innovation Solution
A method and apparatus for tracking facial critical areas involve accessing image frames, detecting facial part coordinates, determining initial coordinate data for critical areas, and using this data to track the critical areas across adjacent frames, thereby reducing computational load and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face detection and critical area positioning are performed on each frame, then tracking accuracy is maintained, but processing time increases and real-time performance deteriorates
Solution Approach 1:
The patent performs face detection and critical area positioning only on the first frame to obtain initial coordinate data, then uses this preliminary information to track the face across subsequent frames without repeated detection, significantly reducing processing time while maintaining tracking accuracy
Solution Approach 2:
The patent creates a coordinate model of the face from the first frame and copies/transforms this model across subsequent frames based on face movement, avoiding the need to re-detect the face in each frame while preserving tracking accuracy
2Reliability
If robust face tracking algorithms are used, then tracking reliability improves, but algorithm complexity increases and processing speed decreases
Solution Approach 1:
The patent segments the face tracking process into two distinct phases: (1) initial face detection and critical area positioning on the first frame, and (2) coordinate transformation and tracking on subsequent frames, simplifying the overall algorithm while maintaining reliability
Solution Approach 2:
The patent changes the processing parameters by performing comprehensive detection only once on the first frame, then using simplified coordinate transformation parameters for subsequent frames, reducing algorithm complexity while maintaining tracking reliability
3Measurement precision
If face detection is performed on every frame, then tracking precision is maintained, but computational load increases and efficiency decreases
Solution Approach 1:
The patent performs the computationally intensive face detection and critical area positioning as a preliminary action on the first frame only, then uses the results to efficiently track the face across subsequent frames with minimal computation, maintaining precision while improving efficiency
Solution Approach 2:
The patent creates a coordinate model from the first frame and copies/transforms it across subsequent frames, avoiding repeated detection computations while preserving tracking precision, thereby significantly improving processing efficiency
Data Source
AI summary
Method, terminal, and storage medium for tracking facial critical area are provided. The method includes accessing a frame of image in a video file; obtaining coordinate frame data of a facial part in the image; determining initial coordinate frame data of a critical area in the facial part according to the coordinate frame data of the facial part; obtaining coordinate frame data of the critical area according to the initial coordinate frame data of the critical area in the facial part; accessing an adjacent next frame of image in the video file; obtaining initial coordinate frame data of the critical area in the facial part for the adjacent next frame of image by using the coordinate frame data of the critical area in the frame; and obtaining coordinate frame data of the critical area for the adjacent next frame of image according to the initial coordinate frame data thereof.