Gesture Recognition Center Point Stabilization Against Hand Shake Jitter
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Solution Overview
Problem
Gesture recognition systems face challenges in accurately detecting dynamic gestures due to unintentional hand shakes, which cause jitter in image frames, affecting the operation experience and recognition accuracy.
Innovation Solution
A method that acquires and processes the coordinates of a gesture's center point in each image frame, determining if it's within a preset region, and if not, calculates the actual center point using specific formulas to stabilize the gesture recognition, ensuring continuity and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If gesture detection is performed on consecutive image frames to recognize dynamic gestures, then gesture recognition capability is improved, but hand shake jitter causes recognition accuracy to deteriorate
Solution Approach 1:
The patent applies preliminary action by predicting the actual center point coordinates before final gesture recognition occurs. The system uses historical center point data and movement trends to pre-calculate compensated coordinates that account for anticipated hand shake jitter, thereby improving recognition accuracy before the actual measurement is finalized
Solution Approach 2:
The patent implements feedback by continuously comparing the detected center point coordinates with the predicted actual center point coordinates across multiple consecutive frames. The system uses this feedback loop to adjust and refine the gesture recognition results, compensating for hand shake effects through iterative correction based on temporal consistency
2Measurement precision
If hand shake compensation is applied to stabilize gesture recognition, then recognition accuracy is improved, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by focusing compensation calculations only on the gesture center point region rather than processing the entire image. The system identifies and compensates specifically for jitter in the critical center point coordinates while leaving other image processing operations unchanged, thereby reducing overall calculation complexity
Solution Approach 2:
The patent uses parameter changes by transforming the hand shake compensation problem into a coordinate system transformation. Instead of complex image processing, the system changes the reference frame parameters (center point coordinates) using mathematical transformations that are computationally efficient while achieving the desired stabilization effect
Data Source
AI summary
The present application provides a gesture recognition method, a device, an apparatus and a storage medium. The gesture recognition method includes: acquiring coordinates of a center point of a gesture in an ith frame of image; determining whether the center point of the gesture in the ith frame of image is within a preset region; if yes, determining that coordinates of an actual center point of the gesture in the ith frame of image are coordinates of an actual center point of the gesture in the (i−1)th frame of image; wherein i is an integer greater than or equal to 2, and the preset region is a region taking the actual center point of the gesture in the (i−1)th frame of image as a center; and performing a dynamic-gesture recognition according to coordinates of an actual center point of the gesture in each frame of image.