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Artificial Intelligence with Python

Artificial Intelligence with Python

By : Prateek Joshi
3.6 (34)
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Artificial Intelligence with Python

Artificial Intelligence with Python

3.6 (34)
By: Prateek Joshi

Overview of this book

Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more. Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
Table of Contents (17 chapters)
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Optical flow based tracking

Optical flow is a very popular technique used in computer vision. It uses image feature points to track an object. Individual feature points are tracked across successive frames in the live video. When we detect a set of feature points in a given frame, we compute the displacement vectors to keep track of it. We show the motion of these feature points between successive frames. These vectors are known as motion vectors. There are many different ways to perform optical flow, but the Lucas-Kanade method is perhaps the most popular. Here is the original paper that describes this technique: http://cseweb.ucsd.edu/classes/sp02/cse252/lucaskanade81.pdf .

The first step is to extract the feature points from the current frame. For each feature point that is extracted, a 3x3 patch (of pixels) is created with the feature point at the center. We are assuming that all the points in each patch have a similar motion. The size of this window can be adjusted depending on the...

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Artificial Intelligence with Python
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