We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
Jangmin O, Jae Won Lee, Sung-Bae Park, Byoung-Tak ...
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Abstract We consider the use of medial surfaces to represent symmetries of 3-D objects. This allows for a qualitative abstraction based on a directed acyclic graph of components an...
Kaleem Siddiqi, Juan Zhang, Diego Macrini, Ali Sho...
We present a 2D model-based approach to localizing human body in images viewed from arbitrary and unknown angles. The central component is a statistical shape representation of th...
Several novel and particularly successful object and object category detection and recognition methods based on image features, local descriptions of object appearance, have recent...
Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paal...