Using generative models for handwritten digit recognition

We describe a method of recognizing handwritten digits by fitting generative models that are built from deformable B-splines with Gaussian ``ink generators'' spaced along the length of the spline. The splines are adjusted using a novel elastic matching procedure based on the Expectation Maximization (EM) algorithm that maximizes the likelihood of the model generating the data. This approach has many advantages. (1) After identifying the model most likely to have generated the data, the system not only produces a classification of the digit but also a rich description of the instantiation parameters which can yield information such as the writing style. (2) During the process of explaining the image, generative models can perform recognition driven segmentation. (3) The method involves a relatively small number of parameters and hence training is relatively easy and fast. (4) Unlike many other recognition schemes it does not rely on some form of pre-normalization of input images, but can handle arbitrary scalings, translations and a limited degree of image rotation. We have demonstrated our method of fitting models to images does not get trapped in poor local minima. The main disadvantage of the method is it requires much more computation than more standard OCR techniques

MathBrush: An Experimental Pen-Based Math System

It is widely believed that mathematics will be one of the major applications for Tablet PCs and other pen-based devices. In this paper we discuss many of the issues that make doing mathematics on such pen-based devices a hard task. We give a preliminary description of an experimental system, currently named MathBrush, for working with mathematics using pen-based devices. The system allows a user to enter mathematical expressions with a pen and to then do mathematical computation using a computer algebra system. The system provides a simple and easy way for users to verify the correctness of their handwritten expressions and, if needed, to correct any errors in recognition. Choosing mathematical operations is done making use of context menus, both with input and output expressions

EFFICIENT QUALITY MANAGEMENT OF HUMAN-BASED ELECTRONIC SERVICES LEVERAGING GROUP DECISION MAKING

Human-based electronic services (people services) provide a powerful way of outsourcing tasks to a large crowd of remote workers over the Internet. Because of the limited control over the workforce in a potentially globally distributed environment, efficient quality management mechanisms are a prerequisite for successful implementation of the people service concept in a business context. Research has shown that multiple redundant results delivered by different workers can be aggregated in order to achieve a reliable result. However, existing implementations of this approach are highly inefficient as they multiply the effort for task execution and are not able to guarantee a certain quality level. Our weighted majority vote (WMV) approach addresses this issue by dynamically adjusting the level of redundancy depending on the historical error rates of the involved workers and the level of agreement among them. A practical evaluation in an OCR scenario demonstrates that the approach is capable of gaining reliable results at significantly lower costs compared to existing procedures

Automatic generation of Chinese calligraphic writings with style imitation

A parametric representation of stroke shapes is derived by adopting style imitation, a shape-generation-based process, to compactly represent the shapes of single strokes for the automatic generation of Chinese calligraphic writings. An image-processing-based approach is employed to derive the distance between the two strokes. The concept of stroke context is introduced to determine the shape of a stroke to be produced and the distance between two strokes is defined as the shortest distance between two points. An important difference between personal handwriting and a script generated from a font system is that a human writer writes a certain stroke or character differently each time, while a font system generates the same output. The shape-based criterion used in this study makes direct use of areas, which is more reliable than using shape contours because stroke contour details vary greatly.published_or_final_versio