Computer Vision Emotion Board Polling System
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Solution Overview
Problem
Existing online polling solutions require individual device access and energy-intensive computing, which can be resource-intensive and impractical for collecting simple feedback, such as students' emotional states in educational settings where not all students have access to devices or software.
Innovation Solution
A software solution that digitizes physical poll responses using computer vision to analyze images of physical polling boards, allowing students to respond anonymously by placing cards on a board, which are then logged and analyzed for insights on social-emotional trends without the need for individual device access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If online polling software is used to collect student feedback, then real-time data collection and analysis capability is improved, but device accessibility requirement increases and energy consumption increases
Solution Approach 1:
The patent uses computer vision to capture images of physical polling boards and creates digital copies of the responses. The system processes photographs of physical cards placed on a board, converting them into structured digital data without requiring respondents to use digital devices. This copying approach maintains real-time data collection while eliminating device accessibility requirements.
Solution Approach 2:
The patent replaces the mechanical/digital system of individual device interaction with an optical system. Instead of students interacting with software on devices, they physically place cards on a board, and the system uses image capture and computer vision algorithms to detect and process the responses. This substitution eliminates the need for each student to have a computing device while maintaining automated data collection.
2Measurement precision
If individual computing devices are provided to each student for polling, then data collection accuracy is improved, but infrastructure cost and resource requirement increase
Solution Approach 1:
The patent merges multiple individual response collection points into a single physical polling board that can be captured by one image. Instead of requiring separate device interactions from each student, all responses are collected on a shared physical surface, and a single photograph captures all responses simultaneously. This merging reduces infrastructure requirements while maintaining data accuracy through computer vision processing.
Solution Approach 2:
The physical polling board serves as a universal interface that can be used by all students without requiring individual devices. The board functions as a shared response surface that accommodates all students' inputs, and the image capture system universally processes all responses in a single operation. This universal approach eliminates the need for multiple individual computing devices while maintaining accurate data collection.
3Adaptability or versatility
If computer vision processing is applied to physical polling boards, then device accessibility is improved, but computational energy consumption increases
Solution Approach 1:
The patent uses preliminary action by capturing all responses in a single photograph before processing begins. The physical responses are frozen in the image, and all computer vision processing operates on this static image rather than requiring continuous interaction. This preliminary capture approach allows energy-intensive processing to occur after data collection, reducing the energy burden during the response collection phase and improving accessibility.
Data Source
AI summary
A computing apparatus comprising: one or more computer readable storage media, one or more processors operatively coupled with the one or more computer readable storage media, and program instructions stored on the one or more computer readable storage media that, when executed by the one or more processors, direct the computing apparatus to at least: receive an image of an emotions board, wherein the emotions board includes a canvas and response cards of group members arranged on the canvas in proximity to polling cards. For at least a response card of the response cards, the program instructions direct the computing device to identify a position of the response card on the canvas, identify an emotion corresponding to the position on the canvas, identify a group member associated with the response card, and log the emotion in association with the group member.