Livestream Background Manipulation via Product Detection
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Solution Overview
Problem
Current livestream video technologies lack the ability to dynamically and automatically change backgrounds based on the products being showcased, limiting engagement and monetization opportunities in an increasingly competitive content environment.
Innovation Solution
A computer-implemented method that analyzes livestream videos to identify foreground objects, defines a virtual background based on the products, and renders a new video stream with the virtual background, which can be dynamically changed and sponsored or auctioned, incorporating features like coupons and promotional offers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual background management is used in livestreams, then simplicity is maintained, but adaptability to different products and monetization opportunities are limited
Solution Approach 1:
The system automatically detects products in the livestream video, retrieves corresponding backgrounds from the database, and composites them without human intervention. The processor independently manages the entire workflow from product detection to background application, enabling the system to serve itself and eliminating the need for manual background management while achieving high adaptability
Solution Approach 2:
The background transitions from a static, manually-selected state to a dynamic, automatically-updated state that changes in real-time based on the products being showcased. The system continuously monitors the livestream content and adjusts backgrounds dynamically, allowing the background to adapt flexibly to different products, scenarios, and promotional requirements
2Productivity
If automatic product detection and background rendering is implemented, then engagement and monetization are enhanced, but processing time and computational resources increase
Solution Approach 1:
Background images are pre-loaded into the database before the livestream begins. When products are detected, the system simply retrieves and composites the pre-prepared backgrounds rather than creating or downloading them in real-time. This preliminary preparation significantly reduces the processing time required during the livestream while maintaining high engagement through dynamic background changes
Solution Approach 2:
The system uses image copying and compositing techniques to overlay detected products onto pre-rendered background templates. Rather than performing complex real-time rendering or generation, the system copies product images and combines them with stored background images through efficient image processing operations, reducing computational overhead and processing time
Data Source
AI summary
Techniques for manipulating video livestream background images are disclosed. A short-form video, such as a livestream video or livestream replay video, can be analyzed for context. Computer-implemented techniques may be used for performing entity detection, and can also detect a change in subject based on speech and/or actions of a host individual. The subject can include a particular product. The detecting a change in subject can include detecting a foreground object and identifying the foreground object as a product. The identification of the foreground object as a product can include performing optical character recognition on text imprinted on a foreground object. The identification of the foreground object as a product can include image recognition techniques. The identification of the foreground object as a product can include scanning of an optical code such as a barcode that is imprinted on the product.