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# Computer Vision Made Easy

Aus der Reihe: Computer Vision with MATLAB

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#### Themenbezogene Videos und Webinare

Avinash Nehemiah, MathWorks

In this introductory webinar you will learn how to use computer vision algorithms to solve real world imaging problems. Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene.

You will discover how to:

• Find moving objects in video
• Analyze the motion of objects
• Detect and locate faces in images and video
• Track a single object over many frames of video

We will demonstrate key features through real world examples including:

• Analyzing the flow of traffic using motion analysis
• Using a person’s movements to interact with a computer
• Locating an object in a cluttered scene

This webinar assumes some experience with MATLAB and no experience with computer vision. We will focus on the Computer Vision System Toolbox.

View example code from the webinar here: http://www.mathworks.com/matlabcentral/fileexchange/45951--computer-vision-made-easy--demo-files

About the Presenter: Avinash Nehemiah works on computer vision applications in technical marketing at MathWorks. Prior to joining MathWorks he spent 7 years as an algorithm developer and researcher designing computer vision algorithms for hospital safety and video surveillance. He holds an MSEE degree from Carnegie Mellon University.

#### Die Arbeitsweise der folgenden Werkzeuge wird gezeigt

• Computer Vision System Toolbox

Aufgezeichnet: 6 Mrz 2014

## Reihe: Computer Vision with MATLAB

Computer Vision Made Easy
In this introductory webinar you will learn how to use computer vision algorithms to solve real world imaging problems. Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene.

Computer Vision with MATLAB for Object Detection and Tracking
Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene. In this webinar, we dive deeper into the topic of object detection and tracking.

Face Recognition with MATLAB
Recognize faces using machine learning and computer vision techniques.