AR Virtual Object Allocation via Image Recognition
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Solution Overview
Problem
Current augmented reality (AR) technologies lack efficient methods for users to distribute and receive virtual objects in real-world environments, resulting in limited interactivity and user experience.
Innovation Solution
An AR client terminal scans the environment to recognize a preset bound target, allowing users to bind virtual objects to specific locations, which can then be discovered and retrieved by others using a live map and image recognition technology.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AR technology overlays virtual objects onto the real world, then user immersion and interactivity are enhanced, but efficient distribution and reception of virtual objects in real-world environments is lacking
Solution Approach 1:
The patent introduces a server as an intermediary component that mediates between distributing users and receiving users. The server manages virtual object distribution, stores binding relationships between virtual objects and location data, and enables efficient transmission of virtual objects without requiring direct peer-to-peer interaction. This resolves the contradiction by providing a centralized coordination mechanism that enhances both interactivity and operational ease.
Solution Approach 2:
The patent replaces traditional mechanical or manual methods of virtual object distribution with automated image recognition and location-based services. The system automatically detects preset bound targets through image scanning, determines user locations via GPS or other positioning mechanisms, and triggers virtual object delivery without manual intervention. This substitution of automated systems for manual processes resolves the contradiction by making virtual object distribution both interactive and operationally simple.
2Adaptability or versatility
If users manually distribute virtual objects, then control over distribution is maintained, but user experience and interactivity are limited
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically performs distribution tasks based on predefined rules and user actions. When a distributing user binds a virtual object to a preset bound target and location, the system autonomously manages the distribution process, including storing binding information on the server, detecting when receiving users are at the correct location through image recognition, and delivering virtual objects without requiring complex manual operations. This self-service approach enhances user experience while keeping the distribution mechanism simple.
Solution Approach 2:
The patent employs preliminary action by requiring distributing users to pre-bind virtual objects to specific locations and preset bound targets before actual distribution occurs. Users configure distribution parameters in advance, and the system automatically executes the distribution when conditions are met (e.g., when receiving users scan the correct image at the designated location). This preliminary configuration simplifies the actual distribution process and enhances user experience by making the system appear magical and effortless.
3Adaptability or versatility
If virtual objects are bound to specific locations, then real-world integration is improved, but detection and recognition of bound targets becomes more difficult
Solution Approach 1:
The patent utilizes visual characteristics of preset bound targets (such as color, shape, or distinctive visual features) to enable easy recognition by receiving users' devices. The system is designed to detect these visual markers through camera scanning, where the preset bound targets are intentionally made visually distinct or recognizable. This approach maintains strong real-world integration through location-based binding while simplifying the detection process through deliberate visual design of recognition targets.
Solution Approach 2:
The patent uses image copying and pattern recognition techniques where the system captures an image of the preset bound target through the device camera and compares it against stored reference images or patterns. The server stores the visual characteristics of bound targets, and when a receiving user scans a location, the system automatically compares the captured image with stored patterns to verify the presence of the correct target. This copying and comparison approach enables accurate recognition while maintaining real-world integration.
Data Source
AI summary
A method of allocating virtual objects based on augmented reality (AR) includes displaying, by an AR client terminal of a receiving user, a live map associated with a location of the receiving user. The live map includes a target location to which a virtual object was bound by a distributing user. The AR client terminal of the receiving user scans an image of an environment of the target location. In response to determining that the scanned image includes a preset bound target, the AR client terminal of the receiving user receives information of the virtual object from a server terminal. The preset bound target is associated with the virtual object and the target location.