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.
Some universities recorded lecture videos, therefore, a variety of researches focus on photo video analysis in order to generate class notes. One practical solution was blackboard segmentation @cite_0 . This system first analyzed video to segment written regions on blackboard. Then it exported these regions of notes in photo format. This solution was effective especially when processing lectures in the past. However, it could only generate photo, which was not a search-friendly content. Another method @cite_17 @cite_15 was to use a camera scanning whole white board with several photos. Then it stitched those images together as a panorama and eliminate background and keep enhanced notes image. This solution was practical and generated readable notes image. There was also a system @cite_21 which could recognize handwriting text from these photo by OCR. However, these two solutions could not automatically generate notes with time line in every line. In real settings, this system might miss content if it missed a single photo. The modification on notes also could not be preserved. Most significantly, the writer must not block the notes on the board, which was hard to achieve during lecture.
@cite_0 @cite_15 @cite_21 @cite_17
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We propose a method for segmentation of written regions on a blackboard in the lecture room using a video image. We first detect the static edges of which locations on the image are stationary. Next, we extract several rectangular regions in which these static edges are located densely. Finally, by use of fuzzy rules, the extracted rectangles are merges as contextual regions, where letters and figures in each contextual region explain each context. We apply our method to automatic production of lecture video, and archives segmentation of written regions on the blackboard in lecture rooms. A whiteboard provides a large shared space for the participants to focus their attention and express their ideas, and is therefore a great collaboration tool for information workers. However, it has several limitations; notably, the contents on the whiteboard are hard to archive or share with people who are not present in the discussions. This paper presents our work in developing tools to facilitate collaboration on physical whiteboards by using a camera and a microphone. In particular, we have developed two systems: a whiteboard-camera system and a projector-whiteboardcamera system. The whiteboard-camera system allows a user to take notes of a whiteboard meeting when he she wants or in an automatic way, to transmit the whiteboard content to remote participants in real time and in an efficient way, and to archive the whole whiteboard session for efficient post-viewing. The projector-whitebord-camera system incorporates a whiteboard into a projectorcamera system. The whiteboard serves as the writing surface (input) as well as the projecting surface (output). Many applications of such a system inevitably require extracting handwritings from video images that contain both handwritings and the projected content. By analogy with echo cancellation in audio conferencing, we call this problem visual echo cancellation, and we describe one approach to accomplish the task. Our systems can be retrofit to any existing whiteboard. With the help of a camera and a microphone and optionally a projector, we are effectively bridging the physical and digital worlds. The paper describes a system for scanning the content on a whiteboard into a computer by a digital camera and also for enhancing the visual quality of whiteboard images. Because digital cameras are becoming accessible to average users, more and more people use digital cameras to take pictures of whiteboards instead of copying manually, thus increasing productivity significantly. However, the images are usually taken from an angle, resulting in undesired perspective distortion. They also contain other distracting regions such as walls. We have developed a system that automatically locates the boundary of a whiteboard, crops out the whiteboard region, rectifies it into a rectangle, and corrects the color to make the whiteboard completely white. In the case where a single image is not enough (e.g., large whiteboard and low-res camera), we have developed a robust feature-based technique to stitch multiple overlapping images automatically. We therefore reproduce the whiteboard content as a faithful electronic document which can be archived or shared with others. The system has been tested extensively, and very good results have been obtained.