Occlusion-Aware Object Permanence in Simulated Environment Models
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Solution Overview
Problem
Simulated environments in applications like virtual reality and robotics face challenges in maintaining accurate representations of objects over time, particularly when objects become occluded, leading to inefficiencies in updating environment models.
Innovation Solution
A method involving image sensors and processors that capture and analyze data to determine if objects are present or occluded, maintaining or removing their representations in the environment model based on image data, ensuring accurate and dynamic object permanence within the simulated environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the environment model is continuously updated with new image data, then the accuracy of object representation is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary actions by capturing image data at multiple timestamps and maintaining a history of object representations before actual environment model updates are needed. This allows the system to pre-process and store object information, reducing the computational burden during real-time updates while maintaining high accuracy.
Solution Approach 2:
The system applies local quality by selectively updating only those portions of the environment model that contain occluded or changed objects, rather than performing full model updates. This targeted approach reduces overall computational complexity while maintaining accuracy for critical regions.
2Reliability
If the system maintains object representations during occlusion, then object permanence is improved, but the risk of maintaining outdated information increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring image data at multiple timestamps and comparing object representations. When an object becomes unoccluded, the system receives feedback from the new image data to update the object representation, ensuring accuracy is restored while maintaining object permanence during occlusion periods.
Solution Approach 2:
The system uses periodic action by checking for object occlusion at regular time intervals (different timestamps). This periodic monitoring allows the system to maintain object representations during occlusion while systematically verifying object status, balancing object permanence with information accuracy.
3Productivity
If the system removes objects not visible in current image data, then the environment model stays current, but objects that are temporarily occluded are incorrectly removed
Solution Approach 1:
The system performs preliminary analysis by examining image data from multiple previous timestamps to determine whether an object was previously visible and is now occluded. This historical context allows the system to distinguish between permanently removed objects and temporarily occluded objects, preventing incorrect removal while keeping the model current.
Solution Approach 2:
The system applies dynamics by making object representations in the environment model dynamic rather than static. Objects can be added, maintained during occlusion, or removed based on their visibility history across multiple timestamps, allowing the model to adapt to changing visibility conditions while maintaining accuracy.
Data Source
AI summary
Systems, methods, and computer program products for managing simulated environments are described. A simulated environment is accessed which represents a physical environment, and representations of objects are included, maintained, or removed in the simulated environment based on whether objects are represented in image data of the physical environment, and based on whether objects are occluded by other objects in the image data of the physical environment. Future occlusion can also be predicted based on motion paths of objects.