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Detection of Traffic Signs and Road Users From a Moving Vehicle
Abstract
The topic of this chapter is the implementation and analysis of vision algorithms for the detection of static and dynamic objects in videos. These algorithms are typically components of the visual perception module of modern driver-assistance systems or even autonomous cars. Whereas the vast majority of today's papers from the vision community use convolutional deep neural networks (CNNs), this chapter explores the more traditional approaches, namely HOG (Histogram of Oriented Gradients) as well as SVM (Support Vector Machine). The static and dynamic objects to be recognized are traffic signs and motorcycles, respectively. These two object classes have been chosen since traffic signs are relatively easy to detect and motorcycles state a much more complex task. Thus, this chapter tackles differently difficult tasks with a single set of algorithms.
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