Viewing Verification Using Facial and Head Pose Analysis
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Solution Overview
Problem
Current methods for determining viewer engagement with media content lack accuracy, as they cannot distinguish between actual and perceived viewing, leading to inaccurate assessments of content value and advertising effectiveness.
Innovation Solution
The use of image classifiers to analyze images of individuals viewing content, calculating a viewing verification metric based on facial and head pose analysis to determine the actual duration and engagement level, providing a more authentic measure of content engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional viewer engagement measurement methods are used, then the assessment process is simple, but the measurement precision is low and cannot distinguish between actual and perceived viewing
Solution Approach 1:
The patent introduces image classifiers as an intermediary tool between the viewer and the measurement system. These classifiers analyze facial images and head pose data to verify actual viewing, serving as a mediator that translates physical viewing behavior into verifiable metrics without requiring direct complex sensor integration with the viewer.
Solution Approach 2:
The patent replaces traditional mechanical or manual viewing verification methods with computer vision-based image analysis. By using image classifiers to process facial images and head pose data, the system substitutes physical measurement mechanisms with optical and computational approaches, achieving higher precision without proportional increases in mechanical complexity.
2Measurement precision
If image classifiers and facial analysis are used to verify viewing, then the measurement precision improves, but the use of energy and computational resources increases
Solution Approach 1:
The patent applies partial action by using image classifiers selectively rather than continuously analyzing all viewer data at full resolution. The system processes facial images and head pose data at sufficient detail to verify viewing occurrence, avoiding excessive computational energy consumption while maintaining adequate measurement precision for verification purposes.
3Measurement precision
If facial and head pose analysis is performed on multiple images, then the viewing verification accuracy improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments the viewing verification process into distinct analytical components: facial image analysis, head pose analysis, and viewing verification metric calculation. By dividing the complex measurement task into separate manageable segments, each handled by specialized image classifiers, the system reduces the overall difficulty of detection and measurement while improving precision through focused analysis of each aspect.
Data Source
AI summary
Techniques for performing viewing verification using a plurality of classifiers are disclosed. Images of an individual may be obtained concurrently with an electronic display presenting one or more images. Image classifiers for facial and head pose analysis may be obtained. The images of the individual may be analyzed to identify a face of the individual in one of the plurality of images. A viewing verification metric may be calculated using the image classifiers and a verified viewing duration of the screen images by the individual may be calculated based on the plurality of images and the analyzing. Viewing verification can involve determining whether the individual is in front of the screen, facing the screen, and gazing at the screen. A viewing verification metric can be generated in order to determine a level of interest of the individual in particular media and images.