Gamified Human Feedback for Roadway Object Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current object detection systems face challenges in obtaining reliable human feedback due to the tedious and unrewarding nature of the process, which hinders the improvement of roadway object recognition accuracy.
Innovation Solution
A system and method that utilizes gamified distributed human feedback through a smartphone-based interface, where users provide feedback on object detection results, updating confidence levels and incorporating a reward system to motivate participation, thereby improving object detection accuracy and user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human feedback is collected to improve object detection accuracy, then detection precision improves, but user engagement decreases due to the tedious and unrewarding nature of the process
Solution Approach 1:
The system implements a feedback loop where user corrections of object detection results are captured and used to retrain the machine learning model. This creates a continuous improvement cycle where human feedback directly enhances detection accuracy, transforming the tedious process into a value-contributing activity for users.
Solution Approach 2:
The patent introduces a gamification layer as an intermediary between the user and the object detection task. By adding game elements such as points, levels, and rewards, the system mediates the interaction to make the feedback process more engaging while still collecting the necessary data to improve detection precision.
2Reliability
If more human feedback is obtained to increase confidence in object recognition, then reliability improves, but time consumption increases due to the manual verification process
Solution Approach 1:
The system applies human feedback selectively rather than requiring verification of all detected objects. By focusing feedback collection on cases where the machine learning model has lower confidence or makes incorrect predictions, the system achieves reliability improvement with reduced time investment from users.
Solution Approach 2:
The gamified interface allows users to provide feedback at their own pace and convenience. Users can correct detection errors whenever they have free time, and the system accumulates these corrections to improve reliability, rather than requiring dedicated time for verification tasks.
3Productivity
If a reward system is implemented to motivate user participation, then productivity improves, but device complexity increases due to the gamification infrastructure
Solution Approach 1:
The smartphone application serves multiple functions: it acts as both the object detection interface and the gamification platform. By leveraging the existing smartphone capabilities for display, input, and networking, the system implements rewards and engagement mechanisms without requiring separate dedicated hardware, thus managing complexity while improving productivity.
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.