3D Hand Gesture Modeling for Realistic VR Object Displacement
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Solution Overview
Problem
Conventional motion capture systems for virtual reality and augmented reality environments are costly, cumbersome, and lack real-time capability due to the use of markers or sensors, and systems with multiple cameras struggle with data analysis, limiting their deployment and user experience.
Innovation Solution
A method for manipulating virtual objects using real motions of hands in a 3D sensory space, capturing hand images, sensing their location, and incorporating them into a virtual reality scene, with features like drift cancellation and virtual pinch force rendering, allowing for realistic interactions such as grasping and stretching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion capture systems use markers or sensors, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts and removes the complex markers and sensors from the motion capture system. Instead of using traditional motion capture equipment with attached markers or sensors on hands, the system uses conventional cameras to capture images of hands in their natural state, processing these images to detect hand location and gestures without any physical attachments.
Solution Approach 2:
The patent creates a virtual copy of the hand's appearance and position in the virtual reality scene. By capturing real hand images and incorporating them into the virtual environment, the system replicates the visual appearance and spatial position of hands without requiring physical sensors, thus achieving measurement precision through image processing rather than physical detection devices.
2Measurement precision
If multiple cameras are used for motion capture, then measurement precision is improved, but data analysis complexity increases
Solution Approach 1:
The patent extracts only the essential visual information from camera images rather than processing complex multi-camera data streams. By using conventional cameras to capture standard images and applying image processing techniques to extract hand location and gesture information, the system achieves accurate measurement without the computational burden of analyzing multiple synchronized camera feeds.
Solution Approach 2:
The patent replaces the mechanical and computational complexity of multi-camera motion capture systems with optical image processing. Instead of using multiple cameras to track markers in three-dimensional space through complex coordinate transformations, the system uses single or multiple conventional cameras to capture images that are then processed using image analysis algorithms to directly determine hand position and gestures.
3Measurement precision
If markers or sensors are worn on hands, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent completely removes markers and sensors from the hands, allowing users to move naturally without any physical attachments. The system captures images of hands in their natural state and processes these images to detect location and gestures, eliminating the interference that markers or sensors would cause to natural movement while maintaining measurement precision through visual processing.
4Measurement precision
If conventional motion capture systems are used, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent replaces the mechanical motion capture infrastructure with optical image processing. By using conventional cameras and processing images through algorithms that detect hand location and gestures directly from visual data, the system achieves real-time performance without the computational overhead of traditional motion capture systems that require synchronization and coordination of multiple cameras and sensors.
Solution Approach 2:
The patent creates virtual representations of hand position and appearance by copying visual information from captured images into the virtual reality scene. This approach allows for real-time updates of hand position and gestures by processing individual images rather than coordinating complex multi-camera data streams, thereby improving productivity while maintaining measurement precision.
Data Source
AI summary
The technology disclosed relates to a method of realistic displacement of a virtual object for an interaction between a control object in a three-dimensional (3D) sensory space and the virtual object in a virtual space that the control object interacts with. In particular, it relates to detecting free-form gestures of a control object in a three-dimensional (3D) sensory space and generating for display a 3D solid control object model for the control object during the free-form gestures, including sub-components of the control object and in response to detecting a 2D sub-component free-form gesture of the control object in the 3D sensory space in virtual contact with the virtual object, depicting, in the generated display, the virtual contact and resulting rotation of the virtual object by the 3D solid control object model.