Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
A prototype-based approach is introduced for action
recognition. The approach represents an action as a se-
quence of prototypes for efficient and flexible action match-
ing in ...
We present a video demonstration of an agent-based test bed application for ongoing research into multi-user, multimodal, computer-assisted meetings. The system tracks a two perso...
Edward C. Kaiser, David Demirdjian, Alexander Grue...