Automated Object Mapping in Video Content for Product Identification
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Solution Overview
Problem
Determining the specific segment of video content that a user's query is directed towards can be difficult, especially when users want additional information about objects or people in video content, such as movies or TV shows, while consuming it.
Innovation Solution
The system automatically identifies and maps objects in video content, determining relationships between objects and actors, and generates a product appearance timeline to provide accurate responses to user queries, allowing users to request information or purchase products without interrupting their video consumption experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system searches through entire video content to identify objects, then comprehensive object detection is achieved, but processing time and computational resources increase significantly
Solution Approach 1:
The patent segments video content into discrete scenes using scene detection algorithms that identify transitions and boundaries. Each scene is then independently processed for object detection, allowing the system to limit the search scope to relevant segments rather than analyzing the entire video content. This segmentation approach maintains detection accuracy while significantly reducing processing time and computational resources.
2Adaptability or versatility
If the system provides detailed information about all objects in video content, then user information needs are met, but system complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary scene detection and object identification during video playback, creating a structured database of objects, actors, and scenes before user queries are submitted. This preliminary processing organizes data in advance, enabling the system to quickly retrieve and provide relevant information without requiring complex real-time analysis when users ask questions about video content.
Solution Approach 2:
The patent introduces an intermediary processing layer that includes scene detection algorithms, object recognition systems, and a knowledge graph that connects objects to their contextual information. This intermediary structure mediates between the raw video content and user queries, organizing data in a way that simplifies information retrieval while maintaining comprehensive adaptability to various user information needs.
3Loss of information
If users interrupt video playback to search for object information, then accurate information is obtained, but viewing experience is disrupted
Solution Approach 1:
The patent implements a self-service system where the automated system continuously monitors video content, detects objects and scenes, and proactively prepares information in the background without requiring user intervention. Users can simply ask questions about objects or scenes, and the system automatically retrieves and presents relevant information while the video continues to play, eliminating the need for users to interrupt playback for information searches.
Data Source
AI summary
Systems, methods, and computer-readable media are disclosed for systems and methods for automated identification and mapping of objects in video content. Example methods may include determining a first set of frames in video content, determining, using one or more object recognition algorithms, a first object present in the first set of frames, determining that a first product corresponding to the first object is present in a product catalog comprising a set of product images, associating a first product identifier of the first product with a video identifier of the video content, and causing presentation of a set of product identifiers associated with the video identifier.