2D Camera Gesture Recognition via Virtual 3D Mapping
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Solution Overview
Problem
Existing gesture recognition systems struggle to accurately recognize gestures performed in 3D space, particularly those requiring depth perception, and are often expensive and complex due to the use of 3D cameras.
Innovation Solution
A method and system utilizing a 2D camera to detect and recognize gestures by capturing and comparing images of a body part's initial and subsequent positions, converting changes in depth into commands, without the need for 3D cameras, thereby reducing cost and complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D cameras are used to track gestures through 3D space, then gesture recognition accuracy in 3D space is improved, but device cost and system complexity increase
Solution Approach 1:
The patent creates a virtual 3D environment that mirrors the physical 3D space by mapping real-world coordinates to virtual coordinates. This allows a 2D camera to capture 3D gesture information by projecting it into a virtual 3D space, eliminating the need for expensive 3D cameras while maintaining gesture recognition accuracy.
Solution Approach 2:
The patent transforms 2D camera images into 3D spatial information by introducing a virtual Z-axis dimension. Through coordinate transformation algorithms, the system maps 2D image coordinates to 3D virtual space coordinates, enabling depth perception and 3D gesture recognition without requiring 3D imaging hardware.
2Measurement precision
If 3D cameras are used to track gestures through 3D space, then gesture recognition accuracy in 3D space is improved, but device cost increases
Solution Approach 1:
The patent replaces expensive 3D camera hardware with inexpensive 2D camera equipment combined with software-based virtual 3D reconstruction. This substitution dramatically reduces device manufacturing cost while maintaining the capability to recognize 3D gestures through coordinate mapping algorithms.
Solution Approach 2:
The system creates a virtual copy of the 3D physical space using 2D camera inputs and mathematical transformations. This virtual 3D environment allows accurate gesture tracking without requiring costly 3D imaging hardware, achieving the same functional result at a fraction of the cost.
3Device complexity
If existing gesture recognition systems are used, then system simplicity is maintained, but ability to recognize depth-based gestures is lost
Solution Approach 1:
The patent extends 2D gesture recognition systems to handle 3D gestures by adding virtual depth dimension through coordinate transformation. The system maps 2D camera coordinates to 3D virtual space, enabling recognition of depth-based gestures like forward and backward swipes while maintaining system architectural simplicity.
Solution Approach 2:
The virtual 3D coordinate system serves multiple functions: it enables both 2D and 3D gesture recognition, provides depth perception, and maintains compatibility with existing 2D camera hardware. This multi-functional approach enhances system versatility without requiring separate 3D recognition subsystems.
Data Source
AI summary
Disclosed methods include a method of controlling a computing device includes the steps of detecting a gesture made by a human user, identifying the gesture, and executing a computer command. The gesture may comprise a change in depth of a body part of the human user relative to the 2D camera. The gesture may be detected via a 2D camera in electronic communication with the computing device. Disclosed systems include a 2D camera and a computing device in electronic communication therewith. The 2D camera is configured to capture at least a first and second image of a body part of a human user. The computing device is configured to recognize at least a first object in the first image and a second object in the second image, identify a change in depth, and execute a command in response to the change in depth.