The Ohio State University
205 Dreese Laboratory
Department of Electrical and Computer Engineering
The Ohio State University
2015 Neil Avenue
Columbus, OH 43210 USA
E-mail: aleix@ece.osu.edu
Phone: (614) 688-8225 or (614) 292-2571
| Short Bio |
Aleix M. Martinez is an associate professor in the Department of Electrical and Computer Engineering at The Ohio State University (OSU), where he is the founder and director of the the Computational Biology and Cognitive Science Lab. He is also affiliated with the Department of Biomedical Engineering and to the Center for Cognitive Science where he is a member of the executive committee. Prior to joining OSU, he was affiliated with the Electrical and Computer Engineering Department at Purdue University and with the Sony Computer Science Lab. He has served as an associate editor of IEEE Transactions on Pattern Analysis and Machine Intelligence and is currently an associate editor of Computer Vision and Image Understanding and an editor of Image and Vision Computing. He has been an area chair for many top conferences and is a Program co-Chair for CVPR 2014 in his hometown, Columbus, OH. He has also served in numerous NSF and NIH review panels and is a regular reviewer for several national and international funding agencies.
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| Tutorials and seminars |
 Video Lectures: Deciphering the Face, CVPR 2011. If you want to cite the work in this presentation, read and cite the paper "Deciphering the Face" listed below. |
Post-doctoral Researcher Position (computer vision) Post-doctoral Researcher Position (face perception) |
| Publications |
| Journal Publications |
A Model of the Perception of Facial Expressions of Emotion by Humans: Research overview and perspectives Learning Deformable Shape Manifolds The Resolution of Facial Expressions of Emotion Computing Smooth Time-Trajectories for Camera and Deformable Shape in Structure from Motion with Occlusion Kernel Optimization in Discriminant Analysis Features versus Context: An approach for precise and detailed detection and delineation of faces and facial features A Computational Shape-based Model of Anger and Sadness Justifies a Configural Representation of Faces Rigid Structure from Motion from a Blind Source Separation Perspective Rotation Invariant Kernels and Their Application to Shape Analysis Emotion Perception in Emotionless Face Images Suggests a Norm-based Representation Low-Rank Matrix Fitting Based on Subspace Perturbation Analysis with Applications to Structure from Motion Modelling and Recognition of the Linguistic Components in American Sign Language Can low level image differences account for the ability of human observers to discriminate facial identity? Who Is LB1? Discriminant Analysis for the Classification of Specimens Using the information embedded in the testing sample to break the limits caused by the small sample size in microarray-based classification Bayes Optimality in Linear Discriminant Analysis
Pruning Noisy Bases in Discriminant Analysis
Spherical-Homoscedastic Distributions: The equivalency of spherical and Normal distributions in classification
Subclass Discriminant Analysis
A Weighted Probabilistic Approach to Face Recognition from Multiple Images and Video Sequences
Where Are Linear Feature Extraction Methods Applicable?
Robust Motion Estimation under Varying Illumination
On Combining Graph-Partitioning with Non-Parametric Clustering for Image Segmentation
Matching Expression Variant Faces
Recognizing Imprecisely Localized, Partially Occluded and Expression Variant Faces from a Single Sample per Class Clustering in Image Space for Place Recognition and Visual Annotations for Human-robot Interaction PCA versus LDA Learning Mixture Models Using a Genetic Version of the EM Algorithm A New Approach to Object-Related Image Retrieval
Conference Publications
Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion Automatic Selection of Eye Tracking Variables in Visual Categorization for Adults and Infants Kernel Non-Rigid Structure from Motion Deciphering the Face Non-Rigid Structure from Motion with Complementary Rank-3 Spaces Bayes Optimal Kernel Discriminant Analysis Active Appearance Models with Rotation Invariant Kernels Support Vector Machines in Face Recognition with Occlusions Face Recognition with Occlusions in the Training and Testing Sets Precise Detailed Detection of Faces and Facial Features
Spherical-homoscedastic Shapes Sparse Kernels for Bayes Optimal Discriminant Analysis
Recovering the Linguistic Components of the Manual Signs in American Sign Language
Selecting Principal Components in a Two-Stage LDA Algorithm
Three-dimensional Reconstruction of Shape and Motion for the Analysis of American Sign Language
A Blind Source Separation Approach to Structure from Motion
Perturbation Estimation of the Subspaces for Structure from Motion with Noisy and Missing Data Evaluation of the Modeling of Local Areas and Errors of Localization in FRGC’05
A Local Approach for Robust Optical Flow Estimation under Varying Illumination
Recognition of Expression Variant Faces Using Weighted Subspaces
Optimal Subclass Discovery for Discriminant Analysis
From Static to Video: Face Recognition Using a Probabilistic Approach
Template-based Recognition of Static Sitting Postures Recognizing Expression Variant Faces from a Single Sample Image per Class Purdue ASL Database for the Recognition of American Sign Language Physical Correlates of Prosodic Structure in American Sign Language Recognition of Partially Occluded and/or Imprecisely Localized Faces Using a Probabilistic Approach Semantic Access of Frontal Face Images: The expression-invariant problem Face Image Retrieval Using HMMs Semantic Access to a Database of Images: An approach to object-related image retrieval
Book Chapters
Face Recognition, Overview Face Recognition, Component-based A Biologically Inspired Model for the Simultaneous Recognition of Identity and Expression Subset Modeling of Face Localization Error, Occlusion, and Expression Physical Correlates of Prosodic Structure in American Sign Language Dimensionality Reduction for Face Recognition Designing and Implementing Real Walking Agents Using Virtual Environments
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