Vision-Based Computer Interface Using 2D Camera Hand Gesture Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing human-machine interfacing technologies using gesture recognition are limited by precision issues with depth sensors, particularly at long distances, and require users to be in specific locations, leading to inefficiencies and user fatigue.
Innovation Solution
A system and method utilizing a 2D camera to detect hand movements and finger positions from any location within its field of view, processing vector signatures to interpret hand states and map them to virtual keyboard inputs without the need for physical devices, allowing flexible and efficient interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If depth sensors are used for gesture recognition, then scene segmentation is simplified, but measurement precision deteriorates at long distances
Solution Approach 1:
The patent transitions from 2D image analysis to 3D spatial reasoning by introducing depth estimation through parallax effects and perspective geometry. The system uses multiple 2D images taken from different positions to reconstruct 3D hand geometry, enabling precise finger detection at long distances without relying on depth sensors.
Solution Approach 2:
The patent replaces mechanical depth sensors with a computational geometry approach using standard 2D cameras. Instead of relying on hardware-based depth measurement, the system uses mathematical models of hand geometry and perspective projection to achieve precise finger position detection.
2Adaptability or versatility
If distant vision is used for gesture recognition, then user flexibility is improved, but measurement precision deteriorates
Solution Approach 1:
The patent uses multi-view 3D reconstruction to maintain finger position precision at long distances. By capturing images from multiple positions and computing spatial relationships, the system achieves accurate finger detection regardless of distance, enabling users to interact from flexible locations.
3Measurement precision
If short distance vision is used for gesture recognition, then measurement precision is improved, but user flexibility deteriorates
Solution Approach 1:
The patent employs 3D spatial reconstruction from multiple 2D views to achieve both precision and flexibility. The multi-view geometry approach allows the system to maintain accurate finger position detection while accommodating various user distances and angles, eliminating the need for fixed positioning.
4Measurement precision
If multiple cameras are used for stereoscopic vision, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent uses standard 2D cameras that capture images of hand shadows and contours. By analyzing the geometry of these 2D projections from multiple positions, the system reconstructs 3D hand structure without requiring expensive stereoscopic cameras or depth sensors, achieving precision through computational methods rather than specialized hardware.
Data Source
AI summary
System and method which allow a user to interface with a machine/computer using an image capturing device (e.g. camera) instead of conventional physical interfaces e.g. keyboard, mouse. The system allows the user to interface from any physical and non-physical location within the POV of the camera at a distance that is determined by the resolution of the camera. Using images of the hand, the system may detect a change of hand states. If the new state is a known state that represents a hit state, the system would map the change of state to a key hit in a row and column of the keyboard and sends the function associated with that key for execution. In an embodiment, the system determines the row based on the rotation of the wrist and/or position of the hand.