AR Object Surface Identification via Depth Map Segmentation
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Solution Overview
Problem
Current augmented reality devices cannot automatically recognize or identify real-world objects within their environment, limiting their ability to generate interactive and context-aware holograms.
Innovation Solution
An augmented reality system that uses a combination of depth sensors, image analysis, and reverse ray-tracing algorithms to create an enhanced depth map of the environment, allowing for real-time identification of objects and their surfaces, enabling interactive holograms that automatically resize and orient based on object dimensions and orientation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If augmented reality devices use basic depth mapping to recognize surfaces, then large surfaces like floors and walls can be identified, but automatic recognition and identification of specific objects and items within the environment cannot be achieved
Solution Approach 1:
The patent segments the environment recognition process into multiple stages: first identifying large surfaces using depth mapping, then detecting specific objects within those surfaces using image analysis, and finally categorizing objects into types (e.g., furniture, electronics, household items). This multi-level segmentation enables both surface and object recognition without overwhelming the system with a single complex task.
Solution Approach 2:
The patent transitions from two-dimensional image analysis to three-dimensional spatial understanding by projecting detected object locations from image coordinates onto the three-dimensional enhanced depth map. This dimensional transformation enables the system to locate objects in 3D space and associate them with corresponding surfaces, thereby achieving both detection and spatial identification.
2Adaptability or versatility
If augmented reality devices create detailed enhanced depth maps with object identification, then context-aware hologram interaction is enabled, but system complexity and processing requirements increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing images to detect edges and contours before full object analysis, and by pre-categorizing objects into type groups (furniture, electronics, etc.). This preliminary processing reduces the computational burden of subsequent detailed analysis and enables faster real-time interaction while maintaining context-aware capabilities.
Solution Approach 2:
The patent introduces an intermediary layer of object type categorization between raw image detection and hologram interaction. Instead of directly mapping every detected object feature to interaction parameters, the system uses object type classification (e.g., identifying an object as 'furniture' or 'electronics') as an intermediary step that simplifies the decision-making process for hologram placement and interaction behavior.
3Ease of operation
If real-time object identification is implemented, then interactive holograms can be dynamically positioned and sized, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by focusing image analysis resources on detecting only the critical features needed for hologram positioning (such as object boundaries, dominant orientations, and key dimensional cues) rather than performing exhaustive analysis of all object properties. This selective detection achieves sufficient accuracy for automatic positioning while reducing processing time.
Solution Approach 2:
The patent replaces traditional mechanical or manual positioning methods with automated computer vision-based detection. Instead of requiring manual specification of hologram position and size, the system uses image processing algorithms to automatically detect object locations, determine orientations, and calculate appropriate hologram dimensions, thereby enabling ease of operation through automated positioning.
Data Source
AI summary
This disclosure describes how to identify objects in an augmented reality environment. More specifically, the various systems and methods described herein describe how an augmented reality device can recognize objects within a real world environment, determine where the object is located, and also identify the various surfaces of the object in real time or substantially real time.