Building on recent work, we investigated the effect of training comprehension on performance across varying representations of uncertainty and varying degrees of visualization interactivity using a simulated course of action selection task.
Jihye Song, Olivia B. Newton, Stephen M. Fiore, Corey Pittman, Joseph J. LaViola, Jr.
Our dynamic time warping based approach for both segmented and continuous data is designed to be a robust, go-to method for gesture recognition across a variety of modalities using only limited training samples.
Eugene M Taranta II, Amirreza Samiei, Mehran Maghoumi, Pooya Khaloo, Corey Pittman, Joseph J. LaViola, Jr.
We introduce a novel technique called gesture path stochastic resampling (GPSR) that is computationally efficient, has minimal coding overhead, and yet despite its simplicity is able to achieve higher accuracy than competitive, state-of-the-art approaches.
Eugene M. Taranta II, Mehran Maghoumi, Corey Pittman, Joseph J. LaViola, Jr.