Marker-Free Hand Gesture Tracking With 3D Capsule Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing motion capture systems are expensive, cumbersome, and often fail to operate in real-time due to the need for markers or bulky equipment, limiting their deployment in pervasive computing environments.
Innovation Solution
A motion sensory control device captures 3D images using cameras to track hand gestures without markers, constructing 3D models from capsule representations, aligning and analyzing these models to interpret gestures as command inputs for machines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If markers or bulky sensors are used for motion capture, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses virtual capsule models as copies/representations of the hand instead of physical markers. The capsule model is a simplified 3D geometric representation that captures essential hand motion characteristics without requiring physical attachments to the user's body, thereby eliminating the need for bulky sensors and markers while maintaining motion tracking precision
Solution Approach 2:
The patent replaces the mechanical marker-based motion capture system with an image processing-based system. Instead of using physical markers that require mechanical tracking equipment, the system uses cameras to capture hand gestures and computationally generates capsule models, substituting mechanical measurement systems with optical and computational approaches
2Measurement precision
If numerous cameras and sensors are deployed for 3D tracking, then measurement precision is improved, but loss of time increases due to data processing volume
Solution Approach 1:
The patent segments the complex hand geometry into simplified capsule-shaped representations. Instead of processing complex 3D point cloud data from multiple cameras, the system extracts essential motion information and represents the hand as a set of capsule models with fewer parameters, significantly reducing computational complexity while maintaining 3D tracking precision
Solution Approach 2:
The patent uses a limited number of cameras (at least one, preferably two or more) strategically positioned to capture sufficient hand gesture information without requiring extensive sensor arrays. The system processes only the essential features needed for gesture recognition rather than all available data, reducing processing time while maintaining measurement precision
3Ease of operation
If marker-free tracking is implemented, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent creates virtual capsule models that copy the essential geometric and motion characteristics of the hand without physical markers. These digital representations are generated by analyzing hand gestures from camera images, capturing position, orientation, and motion information with sufficient precision for gesture recognition while maintaining ease of use
Solution Approach 2:
The patent transforms the measurement approach by changing from tracking physical marker positions to analyzing hand gesture parameters (position, orientation, shape) from image data. This parameter transformation enables marker-free operation while maintaining the precision needed for accurate gesture recognition and interpretation
Data Source
AI summary
The technology disclosed relates to relates to providing command input to a machine under control. It further relates to gesturally interacting with the machine. The technology disclosed also relates to providing monitoring information about a process under control. The technology disclosed further relates to providing biometric information about an individual. The technology disclosed yet further relates to providing abstract features information (pose, grab strength, pinch strength, confidence, and so forth) about an individual.