AI System for Automated 360 Virtual Object Representation
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Solution Overview
Problem
Current methods for creating high-quality 360-degree virtual photographic representations, or 'spins,' are time-consuming, require human expertise, and often result in inconsistent quality due to the need for manual image stitching and editing, especially for sellers like used vehicle dealers who lack access to professional equipment.
Innovation Solution
A machine-learning artificial intelligence system that automatically identifies angles and features in images or videos, stitches them into a coherent spin, and adds interactive hotspots, reducing the need for manual editing and ensuring consistent quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If professional equipment and manual processes are used to create high-quality spins, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces manual mechanical processes (photography, stitching, editing) with an automated computational system using machine learning algorithms. The system automatically captures images, identifies angles, detects features, and assembles spins without human intervention, thereby maintaining high quality while dramatically increasing productivity
Solution Approach 2:
The system performs self-service by autonomously completing all spin creation tasks including image capture, angle identification, feature detection, and assembly. The machine learning model independently processes raw images and generates professional-quality spins without requiring human expertise or manual editing
2Manufacturing precision
If manual image stitching and editing processes are used, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-training machine learning models on large datasets of images and angles. This pre-training enables the system to quickly and accurately identify angles and detect features during actual spin creation, eliminating the need for time-consuming manual analysis while maintaining high precision
Solution Approach 2:
The patent replaces time-consuming manual stitching and editing processes with automated machine learning-based image processing. The system automatically aligns images based on detected angles and features, eliminating hours of manual work while preserving professional quality standards
3Productivity
If automated systems are used to create spins quickly, then productivity is improved, but manufacturing precision deteriorates
Solution Approach 1:
The patent employs advanced machine learning algorithms including convolutional neural networks for angle identification and feature detection. These computational systems process images rapidly while maintaining high accuracy, achieving both speed and quality that neither manual processes nor simple automation can achieve alone
Solution Approach 2:
The system incorporates feedback mechanisms where the machine learning model continuously refines its angle identification and feature detection based on detected patterns and anomalies. This feedback loop ensures high precision in automated spin creation by adjusting processing parameters based on real-time analysis results
Data Source
AI summary
The present disclosure is directed to automatically generating a 360 Virtual Photographic Representation (“spin”) of an object using multiple images of the object. The system uses machine learning to automatically differentiate between images of the object taken from different angles. A user supplies multiple images and/or videos of an object and the system automatically analyzes and classifies the images into the proper order before incorporating the images into an interactive spin. The system automatically classifies the images using features identified in the images. The classifications are based on predetermined classifications associated with the object to facilitate proper ordering of the images in the resulting spin.