Showing papers by "Jacob Eisenstein published in 2003"

Device independence and extensibility in gesture recognition

Abstract: Gesture recognition techniques often suffer from being highly device-dependent and hard to extend. If a system is trained using data from a specific glove input device, that system is typically unusable with any other input device. The set of gestures that a system is trained to recognize is typically not extensible, without retraining the entire system. We propose a novel gesture recognition framework to address these problems. This framework is based on a multi-layered view of gesture recognition. Only the lowest layer is device dependent, it converts raw sensor values produced by the glove to a glove-independent semantic description of the hand. The higher layers of our framework can be reused across gloves, and are easily extensible to include new gestures. We have experimentally evaluated our framework and found that it yields comparable performance to conventional techniques, while substantiating our claims of device independence and extensibility.

Evolving Robocode Tank Fighters

Abstract: In this paper, I describe the application of genetic programming to evolve a controller for a robotic tank in a simulated environment The purpose is to explore how genetic techniques can best be applied to produce controllers based on subsumption and behavior oriented languages such as REX As part of my implementation, I developed TableRex, a modification of REX that can be expressed on a fixed-length genome Using a fixed subsumption architecture of TableRex modules, I evolved robots that beat some of the most competitive hand-coded adversaries