Computer Vision Object Detection for Social Media Remarketing
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Solution Overview
Problem
Social networking systems face challenges in capturing and leveraging off-network user interactions with brands, as traditional advertisements require explicit on-network interactions, missing implicit actions and exposures captured in user-uploaded multimedia content.
Innovation Solution
Implementing computer-vision algorithms to detect concepts in user-uploaded multimedia objects, allowing for the inference of user exposure to products or brands, even without explicit on-network connections, and enabling targeted remarketing to inferred users based on detected objects and locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional advertisements require explicit on-network interactions, then advertising delivery is simple and trackable, but off-network user interactions with brands are missed and marketing coverage is limited
Solution Approach 1:
The patent introduces computer-vision algorithms as an intermediary between user-uploaded multimedia content and advertising delivery. These algorithms automatically detect brands and products in uploaded photos, serving as a mediator that translates implicit off-network interactions into actionable advertising data without requiring explicit user engagement with the advertising system
Solution Approach 2:
The system enables self-service by automatically processing user-uploaded multimedia content through computer-vision algorithms. The algorithms independently detect, recognize, and categorize brands and products in photos without human intervention, then automatically push relevant advertisements to appropriate users based on detected exposures
2Loss of information
If computer-vision algorithms are implemented to detect concepts in user-uploaded multimedia, then implicit off-network interactions are captured, but processing complexity and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-processing user-uploaded multimedia content through computer-vision algorithms immediately upon upload. The system proactively detects and tags brands and products before advertising delivery decisions are made, capturing implicit interactions at the source rather than requiring subsequent manual analysis
Solution Approach 2:
The patent replaces manual or mechanical information capture methods with automated computer-vision algorithms. Instead of requiring users to explicitly tag or report brand exposures, the system uses optical recognition technology to automatically detect and interpret visual information from multimedia content
3Productivity
If explicit on-network interactions are required for advertising, then user intent is clear and targeted, but many potential customers who were exposed to brands off-network are not reached
Solution Approach 1:
The patent implements feedback by using computer-vision detection results to inform and adjust advertising delivery decisions. The system continuously monitors detected brand exposures in user-uploaded content and uses this feedback to push relevant advertisements to users who have demonstrated implicit interest through their multimedia uploads
Data Source
AI summary
Methods, apparatuses and systems directed to detecting objects in user-uploaded multimedia such as photos and videos, determining the location at which the media was captured, inferring a set of users of a social network who were physically present at the time and place of capture, and pushing remarketing content to the set of inferred users for the detected objects, or alternatively, the competitors of the detected concepts.