Perspective Occlusion Estimation in Sensor Simulation
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Solution Overview
Problem
Current methods for simulating sensor systems in virtual test environments are inefficient in detecting perspective occlusion, particularly in real-time applications, due to high computational requirements of existing algorithms.
Innovation Solution
A method that uses a ground truth sensor simulation with a central projection approach to estimate perspective occlusion by projecting virtual objects onto a plane, checking for intersections, and evaluating occlusion based on Euclidean distances, allowing for quick and reliable detection without the need for computationally expensive graphics processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed sensor simulation with realistic image data calculation is implemented, then measurement precision and reliability are improved, but computational effort and processing time increase significantly
Solution Approach 1:
The patent implements a simplified sensor simulation model that performs only the essential function of detecting perspective occlusion rather than calculating complete realistic image data. This partial action approach provides sufficient information for occlusion detection while avoiding the excessive computational effort of full image rendering, thus resolving the contradiction between simulation accuracy and computational efficiency
Solution Approach 2:
The patent uses simplified geometric body representations instead of detailed sensor models. These simplified objects serve the specific purpose of occlusion detection without requiring the computational resources of realistic sensor simulations, effectively trading off detailed accuracy for computational speed in the context of occlusion analysis
2Measurement precision
If comprehensive perspective occlusion detection is implemented, then measurement precision is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent extracts only the essential geometric properties needed for occlusion detection from complex sensor systems. By taking out only the relevant features (position, orientation, field of view parameters) and ignoring unnecessary details, the system achieves accurate occlusion detection without the complexity of comprehensive sensor simulation
Solution Approach 2:
The patent changes the parameter representation from detailed sensor characteristics to simplified geometric body parameters. This parameter transformation reduces complexity by representing sensors as geometric bodies with essential attributes only, while maintaining sufficient accuracy for perspective occlusion detection
3Productivity
If real-time operation is required, then productivity is improved, but measurement precision may be compromised due to limited processing time
Solution Approach 1:
The patent performs preliminary calculations by determining the projection plane and geometric body parameters before the actual occlusion detection. This preliminary setup enables rapid real-time detection during simulation runs, as the computationally intensive preparation work has already been completed and only simple geometric comparisons remain during real-time operation
Data Source
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AI summary
A method for simulating a sensor system with an imaging sensor and an image processing unit. A virtual test environment comprises the sensor and a multitude of virtual objects, a number of which are detectable by the image processing unit. When a first virtual object and a second virtual object detectable by the image processing unit are detected within the sensor's field of view, a projection plane is established. A first geometric body, colocated with the first virtual object and whose dimensions at least approximately match those of the first virtual object, and a second geometric body, colocated with the second virtual object and whose dimensions at least approximately match those of the second virtual object, are projected onto the projection plane using a central projection with the sensor's position coordinates as the viewpoint.If an intersection exists between the images of the first and second geometric bodies, the Euclidean distance between the sensor and the first virtual object is less than the Euclidean distance between the sensor and the second virtual object, and the size of the intersection exceeds a predefined threshold, the second virtual object is assumed to be perspectively occluded. Otherwise, the second virtual object is assumed to be perspectively unoccluded.