Gamified Human Feedback for Roadway Object Detection Confidence
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Solution Overview
Problem
Current object detection systems face challenges in obtaining accurate and efficient human feedback for improving roadway object recognition, as providing feedback is often time-consuming and lacks immediate reward, making it difficult to gather sufficient human input.
Innovation Solution
A system that utilizes gamified distributed human feedback through a smartphone-based interface, where users can provide feedback on object detection results, update confidence levels, and compete with others to improve accuracy, using a database to track user statistics and provide rewards for participation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human feedback is collected to improve object detection accuracy, then measurement precision is improved, but loss of time increases due to the time-consuming nature of manual feedback verification
Solution Approach 1:
The system implements a feedback mechanism where users can verify and correct object detection results through a mobile application. The feedback loop allows users to view detected objects, provide corrections, and update confidence levels, which are then used to continuously improve the object detection algorithm's accuracy over time.
Solution Approach 2:
The system enables users to self-verify detection results through an automated mobile application interface. Users can independently review detected objects, provide feedback, and update confidence levels without requiring manual intervention from developers or system administrators, thereby reducing the time cost of feedback collection.
2Measurement precision
If distributed human feedback is solicited from multiple users, then object detection accuracy is improved, but device complexity increases due to the need for user interface and feedback management systems
Solution Approach 1:
The mobile application serves multiple functions: it displays video content, shows detected objects, collects user feedback, updates confidence levels, and manages user statistics. By consolidating these diverse functions into a single platform, the system reduces overall complexity while enabling distributed human feedback from multiple users.
Solution Approach 2:
The mobile application acts as an intermediary between users and the object detection system. It provides a user-friendly interface for feedback collection, manages communication between users and the system, and handles the complexity of feedback processing, thereby simplifying user interaction while maintaining system accuracy.
3Productivity
If users are motivated through gamification to provide feedback, then productivity of feedback collection is improved, but device complexity increases due to gamification mechanics
Solution Approach 1:
The gamification system dynamically adjusts user experience by providing real-time feedback on detection accuracy, updating confidence levels, and tracking user statistics. The system adapts to user performance and provides evolving challenges and rewards, making feedback collection more engaging and productive while managing complexity through adaptive mechanisms.
Data Source
AI summary
A system comprising a database and a user device. The database may be configured to (i) store metadata generated in response to objects detected in a video, (ii) store a confidence level associated with the metadata, (iii) provide to a plurality of users (a) data portions of the video and (b) a request for feedback, (iv) receive the feedback and (v) update the confidence level associated with the metadata in response to the feedback. The user device may be configured to (i) view the data portions, (ii) accept input to receive the feedback from one of said plurality of users and (iii) communicate the feedback to the database. The confidence level may indicate a likelihood of correctness of the objects detected in response to video analysis performed on the video. The database may track user statistics for the plurality of users based on the feedback.