Virtual Camera Representation Iteration in 3D Simulation
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Solution Overview
Problem
Existing methods for evaluating multiple camera representations in a three-dimensional environment require recalculating the light travel transform, which is time-consuming and resource-intensive, especially when determining camera input and applying different camera settings or vision algorithms.
Innovation Solution
The evaluation of multiple virtual camera representations at the same point-of-view within a three-dimensional environment is achieved without recalculating the light travel transform, using a light capture transform and vision algorithm to generate various representations from a single calculated camera input, thereby accelerating the design and testing of camera and vision components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the light travel transform is recalculated for each camera representation evaluation, then the accuracy of the three-dimensional environment simulation is maintained, but the processing time and computational resources increase significantly
Solution Approach 1:
The light travel transform is calculated in advance and stored in a data structure before multiple camera representation evaluations are performed. This preliminary calculation eliminates the need to recalculate the transform for each camera representation, thereby maintaining simulation accuracy while significantly reducing processing time and computational resource consumption during subsequent evaluations.
2Adaptability or versatility
If multiple camera representations are evaluated with full light travel transform recalculation, then comprehensive testing of camera settings and vision algorithms is achieved, but computational resources and processing time are excessively consumed
Solution Approach 1:
By pre-calculating and storing the light travel transform, the system enables comprehensive evaluation of multiple camera representations and various vision algorithms without repeatedly performing the computationally expensive transform calculation. This allows designers to conduct thorough testing of different camera settings and algorithms while maintaining high design iteration speed.
3Reliability
If the light travel transform calculation is performed repeatedly for different camera representations, then accurate lighting and reflection simulation is maintained, but the system becomes resource-intensive and slow
Solution Approach 1:
The light travel transform is computed once in advance and stored for reuse across multiple camera representation evaluations. This approach maintains the accuracy and reliability of lighting and reflection simulations while dramatically reducing computational resource requirements and system complexity during subsequent camera evaluations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces processing time and resources by calculating camera input once, allowing for efficient testing and tuning of camera settings and vision algorithms, and enables rapid iteration in camera design and simulation.
Implementation Method 1
The infrared light propagates away from the camera, and reflects off of a surface. Some of that reflected light will reflect right back to each pixel location of the camera.
Implementation Method 2
Based on the time that it takes for the emitted light to be received back at each pixel location, and based on the speed of light, the distance to objects can be estimated for each pixel location.
Data Source
AI summary
The evaluation of multiple virtual camera representations at the same point-of-view within a three-dimensional environment without recalculating a light travel transform that represents how light travels and reflects within the three-dimensional environment. These virtual camera representations may include a light capture transform that represents a transform from camera input to camera output. The virtual camera representation may also include a vision algorithm for interpreting the camera output. Thus, different virtual camera representations at the same point-of-view may be used to obtain a variety of representations of the three-dimensional environment at the same point-of-view.