Group Mood Detection via Emotional Indicator Aggregation
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Solution Overview
Problem
Existing technologies lack an efficient method to determine the mood of a group of people using images from mobile computing devices, especially in real-time scenarios like events.
Innovation Solution
A mood detection system that identifies events with multiple attendees, receives indicators such as images or text representing emotions, generates numerical values for these indicators, and aggregates them to determine an aggregate mood of the group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If facial recognition technology is used to determine individual emotions, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple individual emotion detection results into a unified group mood determination. The system aggregates emotional indicators from multiple attendees to produce a single aggregate mood metric, merging individual measurements into a collective assessment that simplifies the overall system function while maintaining precision.
Solution Approach 2:
The system introduces an intermediary processing layer that translates complex facial recognition data into simplified emotional indicators. This intermediary layer processes individual emotion detections and converts them into aggregate mood metrics, reducing the complexity of directly analyzing group emotions while preserving measurement accuracy.
2Productivity
If real-time mood determination is implemented, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs partial analysis by focusing on key emotional indicators rather than comprehensive facial analysis for every attendee. It processes only the essential features needed for mood determination, reducing computational energy consumption while maintaining real-time productivity through selective processing of emotional data.
3Ease of operation
If aggregate mood analysis is performed, then ease of operation is improved, but loss of information increases
Solution Approach 1:
The system extracts only the essential emotional indicators from individual facial analyses to create the aggregate mood. By taking out and retaining only the critical emotional features while discarding redundant individual details, the system simplifies group mood assessment without losing the core information needed for accurate mood determination.
Data Source
AI summary
A system and method for determining a mood for a crowd is disclosed. In example embodiments, a method includes identifying an event that includes two or more attendees, receiving at least one indicator representing emotions of attendees, determining a numerical value for each of the indicators, and aggregating the numerical values to determine an aggregate mood of the attendees of the event.