Titlebook: Vision-based Pedestrian Protection Systems for Intelligent Vehicles; David Gerónimo,Antonio M. López Book 2014 The Author(s) 2014 Computer

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Introduction,PPSs), must detect and track pedestrians, and provide the necessary outputs to the host vehicle in order to prevent potential accidents and even reduce their severity when unavoidable. In this chapter we describe the dawn of these systems in the context of vehicle safety. Then, we introduce the comp

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Classification,es are classified as . or . with the goal of minimizing the number of wrong decisions while maximizing right ones. Broadly speaking, this is a pattern recognition module involving vision and machine learning. The former field dealing with image descriptors and pedestrian models. The later one provid

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Conclusions,it represents a plethora of research papers that have been presented during the last decades, which have progressively enriched the state of the art with faster and improved detectors. At this moment the first vehicles incorporating pedestrian detectors are being presented for mass production. In th

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Book 2014tentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible o

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Completing the System,dules, which are placed at the end of the system’s pipeline and it is the one that generates the output. In addition to reviewing such modules, in this chapter we also review the approaches employed to achieve real-time, which is a global aspect to take into account in a real system.