Augmented Reality Skin Evaluation via Segmentation
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Solution Overview
Problem
Current augmented reality systems lack effective methods for evaluating and debugging the execution of augmented reality skins, making it difficult for users to identify and address undesired features or attributes in real-time.
Innovation Solution
A system and method that utilize a processor to capture initial and evaluation image data, apply skins to modify image data, and generate augmented and evaluation images, allowing users to review the execution of skins by applying a subset of skins to evaluation image data, thereby enabling the identification of specific skins causing undesired features or attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all skins are applied to initial image data to produce augmented data, then the augmented reality overlay is complete, but it becomes difficult to identify and debug specific skins causing undesired features
Solution Approach 1:
The patent segments the evaluation process by applying skins individually or in small groups to the evaluation image data rather than applying all skins simultaneously. This allows the system to isolate and identify specific skins that cause undesired features, making debugging easier while maintaining overall overlay quality.
Solution Approach 2:
The patent extracts problematic skins from the complete augmented reality overlay by using evaluation image data and selectively applying only specific skins. This extraction allows users to identify and separate problematic elements from the complete overlay, enabling targeted debugging without losing the complete functionality.
2Productivity
If skins are applied to modify image data in real-time, then the augmented reality overlay is updated, but it becomes difficult to review and evaluate skin execution
Solution Approach 1:
The patent performs preliminary actions by capturing evaluation image data at different instances of time before finalizing the augmented reality overlay. This allows the system to review and evaluate skin execution details in advance, maintaining real-time update capability while preserving information about skin application for later analysis.
Solution Approach 2:
The patent implements feedback mechanisms by using evaluation image data to review skin execution and providing users with information about how skins were applied. This feedback loop allows users to evaluate skin performance and make adjustments while maintaining real-time overlay updates.
3Adaptability or versatility
If the system processes and applies multiple skins to image data, then the augmented reality functionality is enhanced, but the complexity of evaluating and debugging skin execution increases
Solution Approach 1:
The patent segments the skin evaluation process into manageable steps by processing and applying skins individually or in small groups to evaluation image data. This segmentation reduces the complexity of evaluating and debugging multiple skins while maintaining the enhanced augmented reality functionality.
Solution Approach 2:
The patent uses evaluation image data as an intermediary between the skin application process and the final augmented reality overlay. This intermediary allows the system to evaluate and debug skin execution without adding significant complexity, as the evaluation data serves as a simplified representation for analysis.
Data Source
AI summary
Technologies are generally described for methods and systems effective to produce an evaluation image. In some examples, a processor may receive initial image data generated by light reflected from an object, that corresponds to a real object at a first instance of time. The processor may apply a first skin to modify pixels of features in the initial image data to produce intermediate data and apply a second skin to pixels of features in the intermediate data to produce augmented data. The skins may modify pixels in image data. The processor may receive evaluation image data, used to evaluate execution of the first or second skin, that corresponds to the real object at a second instance of time. The processor may apply the first skin to the evaluation image data to generate evaluation data different from the augmented data.