Normalized Direction Vectors for 3D Scene Viewpoint Representation
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Solution Overview
Problem
Current methods for processing three-dimensional (3D) image data using Cartesian coordinates are inefficient, particularly in situations where 3D understanding of a scene is limited, as they retain more information than necessary and are cumbersome for applications like sporting events where multiple camera perspectives are involved.
Innovation Solution
The approach involves representing object positions using normalized direction vectors and 2D angle coordinates, allowing for the derivation of information from different viewpoints without requiring 3D coordinates, and using a system with a video tracker, object tracker, and data manager to unify and process data from multiple perspectives, enabling the generation of graphical representations and statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D Cartesian coordinates are used to represent object positions, then comprehensive scene understanding is achieved, but processing complexity and information retention requirements increase
Solution Approach 1:
The patent extracts only the necessary directional information from 3D Cartesian coordinates by representing object positions as normalized direction vectors from a camera center. This extraction eliminates the need to retain and process full 3D coordinate information while maintaining the ability to accurately represent spatial relationships and compute measurements from multiple camera perspectives.
Solution Approach 2:
The patent transforms 3D Cartesian coordinate representation into a 2D angular coordinate system by projecting object positions onto a unit sphere. This dimensional reduction from 3D to 2D space maintains comprehensive scene understanding capability while significantly reducing processing complexity and information retention requirements.
2Loss of information
If 3D Cartesian coordinates are used for image processing, then comprehensive spatial information is retained, but storage requirements and processing efficiency decrease
Solution Approach 1:
The patent extracts only the essential directional information needed for spatial representation by using normalized direction vectors. This extraction retains sufficient spatial information for accurate 3D scene understanding and measurement computation while dramatically reducing the amount of data that needs to be stored and processed.
Solution Approach 2:
The patent reduces the dimensionality of spatial representation from 3D Cartesian coordinates to 2D angular coordinates on a unit sphere. This dimensional reduction maintains the necessary spatial information for comprehensive scene understanding while improving processing efficiency and reducing storage requirements.
3Measurement precision
If multiple camera perspectives are processed using 3D coordinates, then accurate 3D measurements can be computed, but the complexity of unifying different viewpoints increases
Solution Approach 1:
The patent creates a universal representation framework using normalized direction vectors that can represent object positions from any camera perspective in a unified manner. This universal representation allows accurate computation of 3D measurements from multiple camera viewpoints without requiring complex viewpoint-specific processing for each camera.
Solution Approach 2:
The patent unifies different camera perspectives by transforming them into a common 2D angular coordinate system on a unit sphere. This unified representation enables consistent computation of 3D measurements across multiple viewpoints while simplifying the complexity of viewpoint unification compared to working with full 3D Cartesian coordinates from multiple cameras.
Data Source
AI summary
Techniques are described for deriving information, including graphical representations, based on perspectives of a 3D scene by utilizing sensor model representations of location points in the 3D scene. A 2D view point representation of a location point is derived based on the sensor model representation. From this information, a data representation can be determined. The 2D view point representation can be used to determine a second 2D view point representation. Other techniques include using sensor model representations of location points associated with dynamic objects in a 3D scene. These sensor model representations are generated using sensor systems having perspectives external to the location points and are used to determine a 3D model associated with a dynamic object. Data or graphical representations may be determined based on the 3D model. A system for obtaining information based on perspectives of a 3D scene includes a data manager and a renderer.