It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
Reliable facial expression recognition by machine is still a challenging task. We propose a framework to recognise various expressions by tracking facial features. Our method uses...
We propose an alternative to probability density classifiers based on normal distributions LDA and QDA. Instead of estimating covariance matrices using the standard maximum likeli...
David M. J. Tax, Piotr Juszczak, Robert P. W. Duin...
We present a practical framework for registering a Mixed Reality(MR) environment of an arbitrary number of agents. Each agent consist of a head mounted display (HMD), which consis...
We present a novel practical method for self-calibrating a camera which may move freely in space while changing it internal parameters by zooming. We show that point correspondenc...
Symbolic Indirect Correlation (SIC) is a nonparametric method that offers significant advantages for recognition of ordered unsegmented signals. A previously introduced formulatio...
Ashutosh Joshi, Daniel P. Lopresti, George Nagy, S...
Fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, Level 1 (pattern), Level 2 (minutiae points) and Level 3 (pores and rid...
Viola and Jones (VJ) cascade classification methods have proven to be very successful in detecting objects belonging to a single class -- e.g., faces. This paper addresses the mor...
Ahmed M. Elgammal, Ramana Isukapalli, Russell Grei...
This paper revisits the model-based approaches for groupwise shape alignment. The key contribution is modeling the landmarks instead of considering them as nodes sliding along the...
We set out an object localization scheme based on a convex programming matching method. The proposed approach is designed to match general objects, especially objects with very li...