We propose a transactional activity model (TAM) for speciication and management of open-ended cooperative activities. In contrast to each of the extended transaction models which focus more on a formal template for data processing patterns in an application, the activity model contains a set of formal templates, namely activity patterns, for capturing patterns of object interactions in an appli...

Dimensionality reduction has long been associated with retinotopic mapping for understanding cortical maps. Multisensory information is processed, fused and mapped to an essentially 2-D cortex in an information preserving manner. Data processing and projection techniques inspired by this biological mechanism are playing an increasingly important role in pattern recognition, computational intell...

A nonlinear probabilistic model of the relaxation labeling (RL) process is implemented in the speaker identi"cation task in order to disambiguate the labeling of the speech feature vectors. In this proposed algorithm, the deterministic labeling of the vector quantization (VQ)-based speaker identi"cation is relaxed by means of introducing initial probabilistic weights to the labeling process of ...

Similarity or likelihood normalization techniques are important for speaker veri"cation systems as they help to alleviate the variations in the speech signals. In the conventional normalization, the a priori probabilities of the cohort speakers are assumed to be equal. From this standpoint, we apply the theory of fuzzy measure and fuzzy integral to combine the likelihood values of the cohort sp...

Locality preserving projection (LPP) is a manifold learning method widely used in pattern recognition and computer vision. The face recognition application of LPP is known to suffer from a number of problems including the small sample size (SSS) problem, the fact that it might produce statistically identical transform results for neighboring samples, and that its classification performance seem...

Illumination and pose invariance are the most challenging aspects of face recognition. In this paper we describe a fully automatic face recognition system that uses video information to achieve illumination and pose robustness. In the proposed method, highly nonlinear manifolds of face motion are approximated using three Gaussian pose clusters. Pose robustness is achieved by comparing the corre...

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear...