Image Processing Computer Vision and Machine Learning

Topics Covered:
1. Linear algebra, probability and MATLAB overview
2. Introduction to Cognitive Vision: Segmentation, Clustering, Classification, Dimensionality Reduction, Regression
3. Probabilistic Modeling and Optimization for Machine Learning and Computer Vision Problems
4. Applications of Computer Vision and Machine Learning: Human articulated tracking and classification, Autiomatic camera Calibration, Person reidentification
5. All the session concepts have hands on training with MATLAB

Not Available

Resource Person: Dr. Vijay JohnToyota Technological Institute, Nagoya, Japan.Postdoctoral Research , University of Amsterdam, Amsterdam worked on machine learning and computer vision project that automatically estimates the camera calibration parameters using human motionPh.D. in Computer Science (Computer Vision),University of Dundee, Dundee, UK M.S. in Information Technology and Robotics,Carnegie Mellon University, Pittsburgh, USA

2 Dec 2013

Not Available

Provided on request