Context-Aware AR Object Prioritization for Occlusion Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image and video analysis algorithms fail to prioritize objects based on the context of the viewer, leading to occlusions that inhibit proper task performance and safety, particularly in augmented and virtual reality environments.
Innovation Solution
An AI system analyzes the contextual situation to assign priority scores to detected objects based on factors like position, type, movement, visibility, and user preferences, using a GAN to modify objects in real-time based on these scores to enhance visibility and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing image and video analysis algorithms are used to detect objects, then object detection is achieved, but objects are not prioritized based on viewer context leading to occlusions that inhibit task performance and safety
Solution Approach 1:
The system changes the parameter of object prioritization by introducing context-based priority scoring. Instead of treating all detected objects equally, the system assigns different priority levels to objects based on contextual factors such as user preferences, object importance, and situational relevance. This parameter change enables the system to resolve occlusions by prioritizing critical objects, thereby improving task performance and safety while maintaining comprehensive object detection capabilities.
Solution Approach 2:
The patent introduces an intermediary component - the priority scoring mechanism - that mediates between object detection and object display. This intermediary layer analyzes contextual information and assigns priority scores to detected objects, which then guides the rendering process to ensure high-priority objects are not occluded. This mediator resolves the contradiction by providing a systematic way to manage object visibility based on contextual importance.
2Loss of information
If all detected objects are displayed equally, then complete object information is provided, but occlusions occur that reduce visibility of important objects
Solution Approach 1:
The system applies local quality by differentiating the visibility treatment of different objects based on their priority scores. Instead of uniform display, high-priority objects receive enhanced visibility treatment (such as being rendered in front of occluding objects or with increased prominence), while lower-priority objects are displayed normally. This localized quality adjustment ensures that important objects remain visible without completely hiding other detected objects, thus maintaining information completeness while improving critical object visibility.
3Illumination intensity
If context-based priority scoring is implemented, then object visibility is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary action by pre-establishing priority scoring criteria and context models before the actual object detection and rendering process. User preferences, object importance weights, and contextual rules are configured in advance, allowing the priority scoring mechanism to operate efficiently during runtime. This preliminary preparation reduces the computational burden during real-time operation, thereby improving object visibility without proportionally increasing system complexity.
Data Source
AI summary
A computer-implemented method for multimedia modification is disclosed. The computer-implemented method includes classifying one or more objects detected within a user's field of view through an augmented reality environment. The computer-implemented method further includes determining a context of the user based, at least in part, on the one or more classified objects detected within the user's field of view. The computer-implemented method further includes generating a priority score for the one or more classified objects based, at least in part, on the context of the user. The computer-implemented method further includes modifying an object detected within the user's field of view based, at least in part, on the priority score of the object.