InfraNotes: Inconspicuous Handwritten Trajectory Tracking for Lecture Note Recording with Infrared Sensors
This addresses the issue of incomplete lecture notes for students, but it is an incremental improvement over existing note-recording methods.
The paper tackles the problem of students missing lecture notes by designing InfraNotes, an infrared sensor system that automatically records notes from a blackboard by tracking lecturer hand gestures without requiring special accessories, and evaluation using character recognition techniques shows it generates clear and complete notes.
Lecture notes are important for students to review and understand the key points in the class. Unfortunately, the students often miss or lose part of the lecture notes. In this paper, we design and implement an infrared sensor based system, InfraNotes, to automatically record the notes on the board by sensing and analyzing hand gestures of the lecturer. Compared with existing techniques, our system does not require special accessories with lecturers such as sensor-facilitated pens, writing surfaces or the video-taping infrastructure. Instead, it only has an infrared-sensor module on the eraser holder of black/white board to capture handwritten trajectories. With a lightweight framework for handwritten trajectory processing, clear lecture notes can be generated automatically. We evaluate the quality of lecture notes by three standard character recognition techniques. The results indicate that InfraNotes is a promising solution to create clear and complete lectures to promote the education.