We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
Outdoor scene classification is challenging due to irregular geometry, uncontrolled illumination, and noisy reflectance distributions. This paper discusses a Bayesian approach to ...
Yanghai Tsin, Robert T. Collins, Visvanathan Rames...
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
A number of studies have demonstrated that infrared (IR) imagery offers a promising alternative to visible imagery due to it's insensitive to variations in face appearance cau...
Results are presented for the largest experimental study to date that investigates the comparison and combination of 2D and 3D face data for biometric recognition. To our knowledg...