Home-Based AR Shopping Through Automatic Room Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing augmented reality systems require users to manually select and position AR elements, which is time-consuming and resource-intensive, detracting from the overall user experience.
Innovation Solution
An AR recommendation system that automatically determines room classification from captured images and intelligently recommends AR elements for display, using a trained neural network classifier to enhance user interaction and reduce resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually select and position AR elements, then precise control over AR element placement is achieved, but user effort and time consumption increase significantly
Solution Approach 1:
The system performs automatic room classification and AR element selection without requiring manual user input. The neural network classifier automatically analyzes captured images to determine room types and selects appropriate AR elements, allowing the system to serve itself rather than requiring continuous user intervention for each AR element placement decision.
Solution Approach 2:
The system pre-classifies rooms and pre-selects AR elements based on room classification before the user needs them. By performing room classification and AR element selection in advance through automated processing, the system prepares the appropriate AR elements for display without requiring users to manually search or select them at the moment of use.
2Adaptability or versatility
If users manually select AR elements, then customization control is maintained, but system resource consumption increases
Solution Approach 1:
The system automatically performs room classification and AR element selection, eliminating the need for users to manually browse and select AR elements. This self-service approach reduces system resource consumption by avoiding the computational overhead of presenting multiple AR element options and processing user selections, while still maintaining adaptability through AI-driven automatic selection.
3Ease of operation
If automated room classification is implemented, then user effort is reduced, but system complexity increases
Solution Approach 1:
The patent replaces manual mechanical operations (user clicking, dragging, and positioning AR elements) with an automated neural network-based classification system. The neural network classifier automatically processes captured images to determine room types and selects appropriate AR elements, substituting the mechanical user interaction process with an intelligent automated system that reduces user effort while managing complexity through specialized AI processing.
Data Source
AI summary
Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving a video that includes a depiction of one or more objects in a room within a home; determining a room classification for the room by processing the one or more objects depicted in the video; selecting one or more augmented reality items available for purchase based on the room classification and the one or more objects depicted in the video; and generating, for display within the video, the one or more augmented reality items that have been selected at a display position within the video corresponding to the one or more objects depicted in the video.