Automated Sentiment Analysis via Video Stream Processing
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Solution Overview
Problem
Businesses face challenges in dynamically assessing customer sentiment towards their facilities, as existing methods rely on post-hoc reviews and lack real-time, granular feedback on service quality and patron emotions.
Innovation Solution
A method and system that analyze video streams of patrons to determine sentiment based on audio and visual cues, generating an overall sentiment value for facilities, which can be updated over time and adjusted for external factors like weather and time of day, allowing for real-time feedback and segmentation of facility areas for improved service optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If businesses use post-hoc reviews to assess customer sentiment, then they can gather feedback on service quality, but they lack real-time insights and granular feedback on patron emotions
Solution Approach 1:
The patent replaces manual post-hoc review collection and analysis with an automated computer vision system that captures video streams, extracts facial expressions and body language, and generates real-time sentiment analysis. This substitution of mechanical human review processes with automated optical and computational systems enables both real-time processing and granular emotional detection.
Solution Approach 2:
The system enables facilities to self-assess customer sentiment automatically without requiring manual intervention for data collection and analysis. The computer vision system continuously monitors patron emotions and generates sentiment reports autonomously, allowing businesses to receive real-time feedback without human operators manually collecting and analyzing reviews.
2Productivity
If businesses implement real-time sentiment analysis using video streams and AI processing, then they gain granular insights into patron emotions, but the device complexity and processing requirements increase
Solution Approach 1:
The patent implements a multi-functional computer vision system that simultaneously performs multiple tasks: capturing video streams from multiple cameras, detecting facial expressions, analyzing body language, identifying spoken words through lip reading, and generating comprehensive sentiment reports. This universal system handles diverse analysis functions within a single integrated platform, managing complexity through consolidation rather than proliferation of separate systems.
Solution Approach 2:
The system segments the complex sentiment analysis task into distinct modular components: video stream processing, facial expression detection, body language analysis, lip reading for word identification, and sentiment aggregation. Each module handles a specific aspect of analysis independently, then results are combined to produce comprehensive sentiment insights. This segmentation manages computational complexity by dividing the overall task into manageable, specialized sub-tasks.
Data Source
AI summary
Embodiments disclosed herein generally relate to a method and system of determining an overall sentiment of a facility. A computing system receives a video stream, including a plurality of frames, of one or more patrons in a facility over a first time period. The video stream includes data indicative of a sentiment of each of the one or more patrons. The computing system parses the plurality of frames to determine the sentiment of the patron based at least on audio and visual cues of the patron captured in the video stream during the first time period. The computing system aggregates one or more sentiments corresponding to the one or more patrons in a data set indicative of an overall sentiment of the facility. The computing system generates a sentiment value corresponding to the overall sentiment of the facility. The computing system outputs the overall sentiment of the facility.