PAOL uses a device to capture the output of a lecturer's computer as it is sent to a projector. Computer vision techniques are then used to determine when significant changes occur and store an image of the material as well as the time when the change occurred. This capture technique works far better, identifying fewer insignificant changes than the best commercial system. Unlike many computer capture systems, PAOL uses image processing techniques to determine significance and is able to determine significant events and generate content from any application displayed on screen.
High-resolution cameras face the front of the lecture room and capture the entire white board space at 15 frames per second. Simple vision techniques are used to locate the lecturer in these frames and to extract a window that centers on the lecturer. These smaller frames are used to create a video of the lecturer. Vision techniques are also used on the images of the front of the room to remove the instructor from the scene in order to better capture material written on the white board. These images are processed to heighten the contrast and sharpness of what is written or drawn on the board. The board images are then analyzed to determine when material has been added, and selected images and the times they appear are saved. Though some similar work has been done with constrained aspect ratio white boards, none has attempted content capture over such large surfaces and with such varied lighting.
This material, with a soundtrack of the lecture, is sufficient to create an indexed presentation from the lecture that is similar to those previously produced by hand. No other system can capture and index material presented on both computer and white board. Also, no white board capture system has been shown to be as robust in accommodating poor lighting, changes in lighting conditions, and other variables.