Video-Based Item Listing Data Extraction
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Solution Overview
Problem
Websites face challenges in identifying and retrieving items uploaded by users when the information is not provided in a standardized structured format, leading to inefficiencies and inaccuracies in search and indexing processes.
Innovation Solution
The technology uses a mobile device camera to capture a video listing of an item, providing input prompts for structured data elements such as orientation, audio inputs for additional information, and dimensional scans, leveraging machine learning to extract relevant data and populate structured data elements, thereby simplifying the item listing process and improving data accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually input structured data for item listings, then data accuracy can be maintained, but user effort and time consumption increase significantly
Solution Approach 1:
The system enables automatic extraction of structured data elements from unstructured video content without requiring manual user input. The video processing system autonomously identifies and extracts item attributes, eliminating the need for users to manually fill out data fields while maintaining high accuracy through AI-based analysis.
Solution Approach 2:
The patent replaces manual mechanical data entry with automated optical and computational systems. Video capture and processing systems automatically extract structured data from unstructured visual content, substituting human manual input with machine-based vision and language processing technologies.
2Reliability
If structured data elements are standardized for all items, then search and identification accuracy improve, but the complexity of the listing process increases
Solution Approach 1:
The system segments the data extraction process into distinct structured data elements (e.g., item name, description, attributes) that can be independently extracted and populated from video content. This segmentation allows the system to handle complex standardized requirements through modular processing of individual data fields.
Solution Approach 2:
The automated system independently handles the complexity of standardized data element extraction without requiring users to understand or manage the underlying structure. The system self-manages the mapping between unstructured video content and standardized data fields, shielding users from complexity while ensuring complete data capture.
3Loss of information
If multiple input requests are provided to users, then comprehensive data collection is achieved, but user interaction complexity and time consumption increase
Solution Approach 1:
The system processes video content continuously to extract multiple structured data elements in a single uninterrupted workflow. Instead of requiring separate user inputs for each data field, the continuous video capture and processing enables simultaneous extraction of all required information from the unstructured content.
Solution Approach 2:
The system autonomously collects comprehensive data from video content without requiring multiple sequential user interactions. The automated processing system independently identifies and extracts all necessary structured data elements from the video, eliminating the need for users to respond to multiple input requests while ensuring complete data collection.
Data Source
AI summary
A web-based item listing platform provides item listings that users can create or search. Item listings can be generated using structured information extracted while capturing an item listing video of the item. During creation of the item listing video, input prompts are provided to the user that cause a mobile device to provide an input request, such as taking an image of a specific feature of the item or providing some other item description information. During the item listing video, image recognition models may also be employed to determine other item description information, such as the color, the brand, and the like. The item listing can be generated from the item listing video by populating a set of structured data elements associated with an item description type. Each structured data element is populated with the item description information corresponding to the associated item description type.