Introduction to Sketch Recognition

-Tracy Hammond and Kenneth Mock

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SUMMARY

The paper presents an overview of the existing technology and ongoing research in the field of sketch recognition (SR). It also enumerates the ways in which SR could make certain tasks simpler and more efficient. It begins with a brief introduction of Ivan Sutherland's sketch pad and a probable reason why it couldn't take off. Raster graphic displays despite their inability to produce smooth lines overshadowed vector graphics (used in sketch pad) due to the flicker free display and lower cost of the former.
Next, types of digitizers (technology used to determine the location of a pen while writing or navigating) are discussed. Passive digitizers use only touch data and don't require a special pen to navigate. However they suffer from various disadvantages like Vectoring (unintended click), jumpy mouse cursor, difficult secondary inputs like right click, and lower resolution. Active digitizers on the other hand use electromagnetic signals reflected off a special pen to get position data, but are free of other disadvantages associated with passive digitizers.
After that, various hardware and software technologies that are used in sketch recognition systems are described. Convertible tablet PCs, slates, Wacom pen tablets are some of the hardware technologies to enable pen based input. Microsoft Vista and XP to some extent have handwriting recognition capabilities. Camtasia screen capture allows users to record their pen interactions.
The next part is related to applications in education. Instructors can deliver their lectures with the help of tablet PCs and large displays. In addition to previously prepared content of their slides, they could show on the fly data by simply sketching on the slides. User studies show that students have shown an increase in performance when such methods were used by instructors. There are few disadvantages associated with this method; one of which is the initial learning curve.
The paper then presents several pointers as to how lectures could be prepared and delivered using the above mentioned technologies. These technologies have found some nice application in describing molecular structure to students, in the field of high school physics and mathematics.
After that the FLUID framework is described. FLUID framework enables end-users to describe their own shapes and domains. So this framework is sustainable and self learning in that way. Users could either describe shapes by entering text data or just by drawing an example shape.
In the end two user studies illustrate how sketch based systems have actually shown positive results in a classroom setting. Statistics show an increase in tablet-PC usage especially in the field of education. So it might not be long before we see tablet PCs installed with sketch recognition systems as a ubiquitous piece of technology in classroom and elsewhere.

DISCUSSION

The paper gives a cursory overview of sketch recognition technology to the uninitiated. I liked the idea of the FLUID framework, where the end-user does not have to wait for a new version every time he wants to work with a new domain. The system can be taught to recognize new shapes. In essence, the intelligence of the system will evolve with usage, very much in line with what humans go through. I was very impressed with the idea of teaching the system a new shape by drawing an example. The text input method, however, would seem a little intimidating to the user.
One more thing that impressed me was the pressure sensitive capabilities of active digitizers. This technology could go a long way in giving digital pens a natural feel of writing pen. I can see it being used by professional painters and artists in future.