Automated AR Content Curation via Highlight Reel Generation
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Solution Overview
Problem
Users often miss AR experiences and content shared by others due to busy lives, leading to low engagement with messaging platforms, and existing technologies lack efficient methods for curating and presenting digital images and videos in a compelling format.
Innovation Solution
The system automatically curates AR content, images, and videos to generate composite AR content items, which are presented in a highlight reel format, utilizing image processing operations, motion sensor input, and machine learning algorithms to enhance user interaction and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users share AR content and digital images through messaging platforms, then the quantity of shared content increases, but user engagement decreases because users miss content due to busy lives
Solution Approach 1:
The system performs preliminary curation of AR content and digital images into highlight reels before users view them. The automated system pre-selects, organizes, and compiles content from multiple users into curated collections, so that when users access the platform, they immediately see relevant, pre-processed content rather than sifting through unorganized shares. This preliminary organization maintains high engagement even as content volume increases.
2Loss of information
If the system presents all shared AR content and digital images, then completeness of content is improved, but the complexity of content delivery increases making it hard for users to find relevant content
Solution Approach 1:
The system segments the large volume of shared AR content and digital images into organized highlight reels grouped by theme, event, or relevance. Instead of presenting all content in a single undifferentiated stream, the system divides content into multiple curated collections, each with a specific focus. This segmentation allows users to navigate through organized categories rather than overwhelming raw data, maintaining completeness while reducing delivery complexity.
Solution Approach 2:
The automated curation system acts as an intermediary between content sharers and content viewers. This intermediary automatically selects, organizes, and presents content in digestible highlight reels, shielding users from the complexity of managing and navigating large volumes of raw content. The intermediary translates unorganized content shares into structured, user-friendly presentations without losing essential content.
3Manufacturing precision
If manual curation of AR content is performed, then the quality of curated content is improved, but the time and resources required increase significantly
Solution Approach 1:
The system implements self-service automated curation using machine learning algorithms that independently analyze, select, and organize AR content and digital images into highlight reels without human intervention. The system serves itself by automatically understanding content relevance, grouping related items, and generating curated collections. This self-service approach maintains high content quality through intelligent algorithms while eliminating the time and resource costs of manual curation.
Solution Approach 2:
The system replaces the mechanical process of manual content curation with automated computational processes. Instead of human curators physically selecting and organizing content, machine learning algorithms and automated systems perform the selection, classification, and compilation tasks. This substitution maintains curatorial quality through intelligent automated decision-making while dramatically reducing the time and human resources required for content curation.
Data Source
AI summary
The subject technology selects a plurality of augmented reality (AR) content items based at least in part on a set of attributes. The subject technology analyzes each of the selected plurality of AR content items to determine an inclusion of textual information, identify an area of interest, or detect panning motion. The subject technology modifies each of the selected plurality of AR content items based at least in part on the analyzing. The subject technology generates, using at least the modified plurality of AR content items, a composite AR content item, the composite AR content item comprising a sequence of different AR content items, each of the different AR content items corresponding to a modified AR content item from the modified plurality of AR content items. The subject technology causes display, at a client device, the generated composite AR content item.