Real-time feature extraction from video stream data for stream ...

Real-time feature extraction from video stream data for stream ...

1. Introduction

Chapter 3 gives a rough introduction to the field of machine learning. Alongside

with some notation, machine learning tasks and algorithms, which are used in

this thesis, get introduced. Furthermore evaluation methods for machine learning

algorithms are presented. In addition the tools, especially RapidMiner and the

streams framework, which play an important role for this thesis, get introduced.

Chapter 4 presents two use cases. Based on these use cases, I tested the above mentioned

video segmentation and tagging techniques. The learning tasks to be solved

in this thesis are defined and quality measurements are established in order to be

able to evaluate the yielded results.

Chapter 5 gives an overview of the datasets that were created for the use cases.

Chapter 6 provides the reader with an overview of possibly extractable features from

video data. The feature extraction has been performed both in a batch mode, using

RapidMiner, and online, using the streams framework.

Chapter 7 contains a documentation of the experiments ran on the previous presented

datasets. All results are evaluated in regard to the quality measurements, which

were defined in chapter 4.

Chapter 8 concludes this thesis by summarizing the yielded results and proposing

topics for future research.


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