19 citations · 26 across the 6 of their papers we have counts for
7 papers
A Fully Bayesian Infinite Generative Model for Dynamic Texture Segmentation
Sahar Yousefi, M. T. Manzuri Shalmani, Antoni B. Chan
Generative dynamic texture models (GDTMs) are widely used for dynamic texture (DT) segmentation in the video sequences. GDTMs represent DTs as a set of linear dynamical systems (LD…
Learning of Tree-Structured Gaussian Graphical Models on Distributed Data under Communication Constraints
Mostafa Tavassolipour, Seyed Abolfazl Motahari, Mohammad-Taghi Manzuri Shalmani
In this paper, learning of tree-structured Gaussian graphical models from distributed data is addressed. In our model, samples are stored in a set of distributed machines where eac…
Learning of Gaussian Processes in Distributed and Communication Limited Systems
Mostafa Tavassolipour, Seyed Abolfazl Motahari, Mohammad-Taghi Manzuri Shalmani
It is of fundamental importance to find algorithms obtaining optimal performance for learning of statistical models in distributed and communication limited systems. Aiming at char…
A Novel Motion Detection Method Resistant to Severe Illumination Changes
Sahar Yousefi, M. T. Manzuri Shalmani, Jeremy Lin +1
Recently, there has been a considerable attention given to the motion detection problem due to the explosive growth of its applications in video analysis and surveillance systems.…
Multilinear Biased Discriminant Analysis: A Novel Method for Facial Action Unit Representation
Mahmoud Khademi, Mehran Safayani, Mohammad T. Manzuri-Shalmani
In this paper a novel efficient method for representation of facial action units by encoding an image sequence as a fourth-order tensor is presented. The multilinear tensor-based e…
Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network
Mahmoud Khademi, Mohammad T. Manzuri-Shalmani, Mohammad H. Kiapour +1
Facial Action Coding System consists of 44 action units (AUs) and more than 7000 combinations. Hidden Markov models (HMMs) classifier has been used successfully to recognize facial…
Analysis, Interpretation, and Recognition of Facial Action Units and Expressions Using Neuro-Fuzzy Modeling
Mahmoud Khademi, Mohammad Hadi Kiapour, Mohammad T. Manzuri-Shalmani +1
In this paper an accurate real-time sequence-based system for representation, recognition, interpretation, and analysis of the facial action units (AUs) and expressions is presente…