March - Tutoriel WOLFRAM Mathematica workshop

Le 10 mars 2016

Salle de réunion CREATIS

Les domaines couverts sont: data processing image processing medical image processing signal processing wavelets statistics numerical computation visualization algorithm scientific editing deployment tools (Cloud, Cdf...)

Information about the speaker: For over twenty years, Dr. Markus van Almsick has been a consultant for Wolfram Research, maker of Mathematica, Wolfram Alpha, Wolfram System Modeler and Wolfram Cloud. He studied theoretical physics at the University of Technology in Munich and at the University of Illinois, and he received a PhD in Biomedical Image Analysis from the Eindhoven University of Technology. For the last six years he has been helping to extend the scope of Mathematica in image and signal processing. Information about the
workshop:
The workshop will include an introduction to Mathematica and how it can be use for data, signal, and image processing. We will showcase a wide range of technologies to connect to data sources and greatly facilitates the import and export of data and dedicated containers — such as EventSeries, TimeSeries, Sound, Image, and Image3D — to host the datasets and powerful functions for data-specific processing, statistic, stochastic, analysis, recognition, and visualization.

This workshop will also feature a long list of signal and image processing highlights as we climb the data-dimensionality ladder implementing captivating application examples: Classical and state-of-the-art algorithms as well as function categories, including morphological processing, color analysis, image filtering, segmentation, geometric transformations, feature detection, and computer vision. Identify pictures, detect people, classify images, read text, segment blobs, and more in just a single line of code. Using built-in data, even the most complicated tasks can be completed in just a few lines of code.

During the workshop we will show you how to extract the pulse of a person in a video sequence using an ordinary built-in camera. This example walks you through the project workflow of a real-world image processing application, including video acquisition and stabilization, skin and face detection, and signal processing.