Hypernetwork Digital Signature for AR Object Identification
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Solution Overview
Problem
Current Augmented Reality (AR) approaches, particularly those involving 3D mapping and 3D positioning, face scalability issues due to high processing demands for real-time data handling, especially in handling invariances like pose, scale, lighting, weather, and occlusion.
Innovation Solution
A method utilizing a hypernetwork-based signature encoding module to generate digital signatures that represent objects of interest and include parameters to define processing for a query processing neural network, enhancing image processing and compression, and improving object identification within images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D mapping and 3D positioning approaches are used for AR enhancements, then object identification accuracy is improved, but processing power requirements and system complexity increase significantly
Solution Approach 1:
The patent extracts the essential object representation into a compact digital signature format, separating the critical identification information from the full 3D point cloud data. This allows accurate object identification while dramatically reducing the data volume and processing requirements compared to maintaining complete 3D mappings.
Solution Approach 2:
The patent creates a simplified digital signature copy of the object that captures essential identifying features without replicating the full complexity of 3D positioning data. This signature serves as a lightweight representation that maintains identification accuracy while reducing processing burden.
2Reliability
If digital signatures include functional parameters to handle invariances, then object identification robustness is improved, but digital signature size and processing complexity increase
Solution Approach 1:
The patent incorporates specific parameter transformations that account for common invariances such as pose, scale, lighting, weather, and occlusion. By pre-computing and encoding these parameter adjustments in the digital signature, the system achieves robust object identification without requiring complex real-time processing to handle these variations.
Data Source
AI summary
A method, apparatus and computer program product generate and utilize a digital signature to identify an object of interest. The method includes providing a reference image depicting the object to a signature encoding module having a hypernetwork. An indication of the object within the reference image is also provided. The method includes generating, with the signature encoding module, the digital signature representing the object. The digital signature includes parameter(s) configured to define processing to be performed by another neural network. The method includes providing the digital signature and at least one query image to a query processing module having a neural network. The method includes identifying, by the query processing module, the object within the at least one query image based upon the digital signature by processing the at least one query image with the neural network of the query processing module in a manner defined by the parameter(s).