VR Object Rendering via Confidence Metric Prioritization
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Solution Overview
Problem
In virtual reality systems, combining image data from different capture devices can lead to inaccuracies such as distortion, loss, or replication of objects, especially when rendering familiar or important objects, due to inconsistencies and the challenge of real-time image processing.
Innovation Solution
A virtual reality system that prioritizes image data from capture devices based on confidence metrics to accurately represent pre-modeled objects, such as faces or logos, by generating a rendered image dataset that favors the image dataset with the higher confidence metric, ensuring accurate and faithful reproduction of these objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image data from multiple capture devices is combined in real-time to render virtual reality data, then the system can provide diverse viewing angles and immersive experiences, but inaccuracies such as distortion, loss, or replication of objects occur due to data inconsistencies and processing challenges
Solution Approach 1:
The patent applies local quality by treating pre-modeled objects differently from other scene elements. When a pre-modeled object is detected, the system selectively prioritizes image data from capture devices that provide accurate representations of that specific object, rather than uniformly combining all incoming data. This localized approach ensures high fidelity for important objects while maintaining the benefits of multi-device data fusion for the overall scene.
Solution Approach 2:
The patent introduces a pre-modeled object database as an intermediary reference system. This database contains prior knowledge about important objects in the scene, acting as a mediator to guide the selection and prioritization of image data from multiple capture devices. By comparing incoming image data against this intermediary reference, the system can identify which data sources provide the most accurate representations of pre-modeled objects.
2Productivity
If image data from multiple capture devices is processed in real-time, then live virtual reality experiences can be provided, but rendering inaccuracies occur due to the challenge of performing large amounts of image processing in real time
Solution Approach 1:
The system applies local quality by concentrating computational resources on accurately rendering pre-modeled objects rather than uniformly processing all scene elements. By identifying which objects are pre-modeled and prioritizing their accurate representation, the system achieves high rendering fidelity for important elements while maintaining real-time performance through selective processing.
Solution Approach 2:
The patent employs preliminary action by pre-identifying and pre-modeling important objects in the scene before the virtual reality experience begins. This advance preparation creates a reference framework that guides real-time image data selection and processing, allowing the system to quickly and accurately render these objects without performing complex analysis during real-time operation.
3Adaptability or versatility
If image data from different vantage points is combined to render new image data, then users can experience real-world places from difficult-to-reach locations, but inaccuracies such as object distortion or replication occur due to inconsistencies between data from different capture devices
Solution Approach 1:
The patent applies local quality by selectively prioritizing image data from specific capture devices based on their vantage points relative to pre-modeled objects. Rather than uniformly combining data from all devices, the system identifies which capture devices provide the most accurate views of important objects and gives those data sources higher weight, ensuring consistent and reliable object representation across different rendered vantage points.
Solution Approach 2:
The pre-modeled object database serves as an intermediary reference that mediates between multiple capture device data streams. By comparing incoming image data against this established reference model, the system can objectively determine which data sources provide accurate representations and prioritize them accordingly, ensuring consistency across different rendered views.
Data Source
AI summary
An exemplary virtual reality system determines a first confidence metric representing an objective degree to which a pre-modeled object is recognized within a first captured image depicting a scene from a first vantage point. The virtual reality system also determines a second confidence metric representing an objective degree to which the pre-modeled object is recognized within a second captured image depicting the scene from a second vantage point distinct from the first vantage point. The virtual reality system then generates a rendered image that includes a depiction of the pre-modeled object from a third vantage point distinct from the first and second vantage points. The depiction of the pre-modeled object is generated based on data from the first and second captured images, the data prioritized for the depiction of the pre-modeled object according to relative magnitudes of the first and second confidence metrics. Corresponding methods and systems are also disclosed.