Gesture Recognition Device Using Extraction and Mechanics Substitution
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Solution Overview
Problem
Existing gesture recognition technologies in augmented reality devices require complex and power-consuming function modules, leading to increased weight, battery drain, and latency, as well as hardware configuration constraints that hinder simple gesture recognition.
Innovation Solution
A gesture recognition device comprising an image extraction device, storage circuit, and recognition circuit that extracts and processes gesture images using deep learning algorithms to select static or dynamic gesture patterns, enabling intuitive and efficient gesture recognition without the need for complex hardware configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If powerful function modules and Lidar with multiple lenses are used for gesture recognition, then gesture recognition accuracy is improved, but device weight and complexity increase
Solution Approach 1:
The patent extracts the gesture recognition function from complex hardware (Lidar, multiple lenses, powerful function modules) and implements it using a simplified camera-based system with image processing algorithms. The core recognition logic is separated from the sensing hardware, allowing accurate gesture recognition with minimal hardware requirements.
Solution Approach 2:
The patent replaces the mechanical/optical complex system (Lidar with multiple lenses) with a simpler camera-based optical system combined with digital image processing. The mechanical complexity of multiple lenses and Lidar components is substituted with a single camera and algorithmic processing, maintaining recognition accuracy while reducing hardware complexity.
2Measurement precision
If powerful function modules are used for gesture recognition, then gesture recognition accuracy is improved, but energy consumption increases
Solution Approach 1:
The patent extracts the computationally intensive gesture recognition function from power-consuming hardware modules and implements it through efficient image processing algorithms on a standard processor. This separation allows accurate recognition while avoiding the continuous high power consumption of dedicated powerful function modules.
Solution Approach 2:
The patent uses a standard camera and conventional processor instead of expensive, power-consuming dedicated gesture recognition modules. The system achieves accurate recognition using readily available, lower-power components, effectively replacing high-power modules with more energy-efficient alternatives.
3Measurement precision
If powerful function modules are used for gesture recognition, then gesture recognition accuracy is improved, but device weight increases
Solution Approach 1:
The patent extracts the gesture recognition capability from heavy dedicated hardware modules and implements it using a lightweight camera system with software-based processing. This extraction eliminates the need for heavy Lidar units and multiple precision lenses, achieving accurate recognition with minimal added weight.
Solution Approach 2:
The patent replaces heavy mechanical/optical systems (Lidar with multiple lenses) with a lightweight camera and digital processing system. The physical weight of multiple precision optical components is substituted with a single camera sensor and algorithmic processing, maintaining recognition accuracy while dramatically reducing device weight.
4Measurement precision
If powerful function modules are used for gesture recognition, then gesture recognition accuracy is improved, but operation latency increases
Solution Approach 1:
The patent extracts the gesture recognition function from complex multi-module systems and implements it as a streamlined image processing pipeline. This extraction creates a more direct processing path from image capture to recognition result, reducing the time delays associated with coordinating multiple powerful function modules.
Solution Approach 2:
The patent replaces complex mechanical/optical systems with multiple moving parts (Lidar scanning mechanisms, multiple lens adjustments) with a static camera and digital processing system. This substitution eliminates mechanical response delays and reduces processing latency while maintaining recognition accuracy through algorithmic efficiency.
Data Source
AI summary
An embodiment of the invention provides a gesture recognition device. The gesture recognition device may include an image extraction device, a storage circuit and a recognition circuit. The image extraction device may extract a first gesture image. The storage circuit may store a plurality of gesture patterns. The recognition circuit may obtain the first gesture information corresponding to the first gesture image according to the first gesture image, select a gesture pattern corresponding to the first gesture image from the gesture patterns according to the first gesture information, and perform the function that corresponds to the selected gesture pattern.