46416118
Active hand tracking
This paper describes a system which uses multiple visual processes to detect and track hands for gesture recognition and human-computer interaction. This system is based on an architecture in which a supervisor selects and activates visual processes. Each process provides a confidence factor which makes it possible for the system to dynamically reconfigure itself in response to events in the scene. Visual processes for hand tracking are described using image differencing and normalized histogram matching. The result of hand detection is used by a recursive estimator (Kalman filter) to provide an estimate of the position and size of the hand. The resulting system provides robust and precise tracking which operates continuously at approximately 5 images per second on a 150 megahertz Silicon Graphics Indy.
46312706
Automatic handwriting gestures recognition using hidden Markov models
Hidden Markov models have been successfully employed in speech recognition and, more recently, in sign language interpretation. They seem adequate for visual recognition of gestures. In this paper, two problems often eluded are considered. We propose to use the Bayesian information criterion in order to determine the optimal number of model states. We describe the contribution of continuous models in opposition to symbolic ones. Experiments on handwriting gestures show recognition rate between 88% and 100%.
206630030
Statistical Gesture Recognition Through Modelling of Parameter Trajectories
The recognition of human gestures is a challenging problem that can contribute to a natural man-machine interface. In this paper, we present a new technique for gesture recognition. Gestures are modelled as temporal trajectories of parameters. Local sub-sequences of these trajectories are extracted and used to define an orthogonal space using principal component analysis. In this space the probabilistic density function of the training trajectories is represented by a multidimensional histogram, which builds the basis for the recognition. Experiments on three different recognition problems show the general utility of the approach.
6708049
Understanding New Metaphors
Metaphors are widespread in natural language. Most natural language processing systems have failed to adequately deal with this issue. A two part approach to this problem involving a Metaphoric Lexicon and a dynamic extension system is described. The extension mechanism operates by analogically mapping previously understood mappings to account for new uses based on known regularities in the English metaphor system. A system based on this approach has been applied to the UNIX domain. Results indicate that this domain exhibits all the predicted regularities and that understanding new senses is possible using these regularities
15290012
Shallow Semantic Parsing using Support Vector Machines
In this paper, we propose a machine learning algorithm for shallow semantic parsing, extending the work of Gildea and Jurafsky (2002), Surdeanu et al. (2003) and others. Our algorithm is based on Support Vector Machines which we show give an improvement in performance over earlier classifiers. We show performance improvements through a number of new features and measure their ability to generalize to a new test set drawn from the AQUAINT corpus.
5918485
A framework for dynamic Byzantine storage
We present a framework for transforming several quorum-based protocols so that they can dynamically adapt their failure threshold and server count, allowing them to be reconfigured in anticipation of possible failures or to replace servers as desired. We demonstrate this transformation on the dissemination quorum protocol. The resulting system provides confirmable wait-free atomic semantics while tolerating Byzantine failures from the clients or servers. The system can grow without bound to tolerate as many failures as desired. Finally, the protocol is optimal and fast: only the minimal number of servers - 3f + 1 - is needed to tolerate any f failures and, in the common case, reads require only one message round-trip.
33984452
Using System Networks to Build Rhetorical Structures
We are currently engaged in a project to study the generation of instructional texts for common consumer devices. Our initial efforts have focused on an exhaustive corpus-based analysis of instruction booklets for cordless telephones. In this paper, we present our analysis of the way the various processes used in this domain are expressed. Our emphasis here is on the relationship between the surface grammatical coding of these processes and the underlying rhetorical structure of the text. This analysis has been formalized using a systemic-functional framework, with the resulting system networks forming the basis for the Imagene text generation system.
39279518
Representing UNIX Domain Metaphors
The language used to describe technical domains like UNIX is filled with metaphor. An approach to metaphor, based on theexplicit representation of knowledge about metaphors, has beendeveloped. MIDAS (Metaphor Interpretation, Denotation, andAcquisition System) is a computer program that that has been developedbased upon this approach. MIDAS can be used to representknowledge about conventional metaphors, interpret metaphoric languageby applying this knowledge, and dynamically learn new metaphors asthey are encountered during normal processing.