Real-Time 3D Synthetic Model Using Point Cloud Curvature
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Solution Overview
Problem
Current methods for creating real-time 3D synthetic models of dynamic physical entities are limited in their ability to accurately track motion and provide realistic visual and auditory representations, especially when dealing with dynamic and complex surfaces like humans or animals, as they often require maintaining topological consistency and struggle with integrating additional information like internal organs and physiological data.
Innovation Solution
The method involves extracting a plurality of points from 3D information depicting a dynamic physical entity, calculating principal curvatures, and generating a continuous surface using ellipsoidal shapes textured with photometric information, while also integrating audio and physiological data to create a realistic synthetic model that can track motion and display emotional states, using point-based geometry and OpenGL for rendering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mesh-based modeling techniques are used to create real-time 3D synthetic models, then topological consistency can be maintained, but the ability to accurately track motion and provide realistic visual representations of dynamic surfaces is limited
Solution Approach 1:
The patent segments the continuous surface into discrete point clouds, where each point represents a local surface element with its own photometric and geometric properties. This segmentation allows independent tracking of each point's motion while collectively representing the full surface, resolving the contradiction between maintaining topological consistency and achieving accurate motion tracking.
Solution Approach 2:
The patent transitions from traditional 2D mesh representations to 3D point cloud representations with full spatial coordinates and photometric information. This dimensional enhancement allows for more accurate representation of dynamic surfaces and motion tracking while maintaining computational efficiency for real-time rendering.
2Stability of the object's composition
If mesh-based modeling is used to represent dynamic surfaces, then a continuous surface can be maintained, but the flexibility to integrate additional information like internal organs and physiological data is reduced
Solution Approach 1:
The patent segments the representation into independent point elements that can be selectively populated with different types of data (geometric, photometric, physiological, internal organs). This modular approach maintains surface continuity through dense point sampling while enabling flexible integration of multiple information types at the point level or through associated metadata.
Solution Approach 2:
The point cloud data structure serves multiple functions simultaneously: it represents the surface geometry, enables photometric rendering, tracks motion, and can associate physiological and internal organs data. This multi-functionality resolves the contradiction between maintaining surface continuity and enabling versatile data integration.
3Manufacturing precision
If point-based geometry with ellipsoidal shapes is used to generate continuous surfaces, then realism and flexibility are improved, but computational complexity increases
Solution Approach 1:
The patent uses ellipsoidal shapes to represent points on the surface, which naturally capture local curvature and lighting variations. This geometric choice improves visual realism by accurately representing surface orientation and reflectivity while maintaining computational efficiency through analytic solutions for ellipsoid rendering and intersection tests.
Solution Approach 2:
The patent creates simplified ellipsoidal copies of surface points rather than computing full high-resolution geometry. These ellipsoidal representations capture the essential visual and geometric properties needed for realistic rendering while significantly reducing computational complexity compared to detailed mesh models.
Data Source
AI summary
A method of creating a real time synthetic model tracking a dynamic physical entity, comprising:a) Receiving multiple points extracted from a sequence of 3D information depicting a dynamic physical entity, each point is associated with position and photometric information.b) Identifying, within the multiply of points, a cloud point which includes multiple entity representative points which portray a surface of the dynamic physical entity.c) Generating a points-surface for a synthetic model by creating spatial presentation of the entity representative points through calculation of principal curvatures for each entity representative point according to the respective position information.d) Generating a continuous surface for the synthetic model by texturing ellipsoidal shapes created for each entity representative point according to the respective photometric information.e) Tracking motion of the dynamic physical entity by adjusting the points-surface and the continuous surface through iterations wherein in each iteration steps a)-d) are performed.