Vision-Based Outdoor Ad Measurement for Viewer Attention Analysis
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Solution Overview
Problem
Outdoor advertising effectiveness is challenging to measure accurately due to difficulties in determining viewer attention and impact, lacking precise metrics beyond traditional estimations.
Innovation Solution
An apparatus and method using vision sensors, AI technology, and data analysis to capture and analyze images or videos of individuals and vehicles within the visibility range of advertising media, quantifying metrics such as viewing duration and attention, and sharing data among multiple sensors for targeted advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional traffic analysis methods are used to estimate outdoor advertising effectiveness, then the evaluation process is simple and cost-effective, but the measurement precision is insufficient and relies on assumptions rather than objective data
Solution Approach 1:
The patent replaces traditional mechanical traffic counting methods with vision sensors and AI-based image analysis systems. The vision sensors capture images and videos of pedestrians and vehicles, while AI algorithms automatically analyze these visual data to determine exposure, viewing, and attention states, thereby achieving precise measurement without manual intervention
Solution Approach 2:
The patent introduces vision sensors as intermediary devices between the advertising media and the analysis system. These sensors act as mediators that capture visual information about passersby and transmit it to the analysis system, enabling indirect but accurate measurement of advertising effectiveness without direct interaction with viewers
2Measurement precision
If vision sensors and AI analysis are deployed to accurately measure viewer engagement, then the measurement precision improves significantly, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary actions by pre-defining criteria for exposure, viewing, and attention states before actual measurement. The system establishes what constitutes each state in advance (e.g., specific head orientations, viewing durations), enabling automated and consistent analysis of viewer engagement without complex real-time decision-making
Solution Approach 2:
The patent segments the complex task of measuring advertising effectiveness into distinct components: exposure detection (whether someone is present), viewing detection (whether someone is looking), and attention detection (whether someone is paying attention). This segmentation allows each aspect to be analyzed independently using specific AI algorithms, reducing overall complexity
3Reliability
If data from multiple advertising media sensors is shared and integrated, then the completeness and accuracy of pedestrian flow prediction improves, but the system complexity and data management requirements increase
Solution Approach 1:
The patent merges data from multiple advertising media sensors into a unified pedestrian flow prediction model. By combining visual data from different locations and perspectives, the system creates a comprehensive view of pedestrian movement patterns, improving prediction reliability through data aggregation and cross-validation
Data Source
AI summary
An apparatus and method for measuring the advertising effectiveness of an advertising medium provides users with advertising analysis data and measurement results in real time. In some examples, the apparatus captures an image or video of an individual, a space, or a vehicle located within a visibility range of the advertising medium using a vision sensor; analyzes the captured image or video at a computing device; and transmits the analyzed results, including advertising effectiveness measurement results, to a user's terminal device or a server; thereby enabling the users (e.g., advertisers, advertising agencies, media owners) to implement various advertising strategies to optimize their campaigns.