detection moving objects spatio temporal de rabe clemens (5 resultados)

Condición: Sehr gut. Zustand: Sehr gut | Seiten: 168 | Sprache: Englisch | Produktart: Sonstiges.

Taschenbuch. Condición: Neu. Neuware -Driver assistance systems of the future require a thorough understanding of the car's environment. In this thesis, a novel principle (6D-Vision) is presented and investigated in detail, which allows the reconstruction of the 3D motion field from the image sequence obtained by a stereo camera system. Given correspondences of stereo measurements over time, this principle estimates the 3D position and the 3D motion vector of selected points using Kalman Filters, resulting in a real-time estimation of the observed motion field. To estimate the absolute motion ¿eld, the ego-motion of the moving observer must be known precisely. Thus, a novel algorithm to estimate the ego-motion from the image sequence is presented. As the 6D-Vision principle is not restricted to particular image processing algorithms, various optical ¿ow and stereo algorithms are evaluated. In addition, two novel scene ¿ow algorithms are introduced, measuring the optical ¿ow and stereo information in a combined approach. This yields more precise and robust results. The application to real-world data, including a demonstrator vehicle for autonomous collision avoidance, is illustrated throughout the thesis.Books on Demand GmbH, Überseering 33, 22297 Hamburg 168 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rabe Clemenswas born in 1979 in Giessen, Germany. He attained his diploma degree in computer engineering from the University of Applied Sciences Wuerzburg, Germany in 2005. In 2011, he was awarded his PhD in computer science from the U.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Driver assistance systems of the future require a thorough understanding of the car's environment. In this thesis, a novel principle (6D-Vision) is presented and investigated in detail, which allows the reconstruction of the 3D motion field from the image sequence obtained by a stereo camera system. Given correspondences of stereo measurements over time, this principle estimates the 3D position and the 3D motion vector of selected points using Kalman Filters, resulting in a real-time estimation of the observed motion field. To estimate the absolute motion field, the ego-motion of the moving observer must be known precisely. Thus, a novel algorithm to estimate the ego-motion from the image sequence is presented. As the 6D-Vision principle is not restricted to particular image processing algorithms, various optical ow and stereo algorithms are evaluated. In addition, two novel scene ow algorithms are introduced, measuring the optical ow and stereo information in a combined approach. This yields more precise and robust results. The application to real-world data, including a demonstrator vehicle for autonomous collision avoidance, is illustrated throughout the thesis. 168 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Driver assistance systems of the future require a thorough understanding of the car's environment. In this thesis, a novel principle (6D-Vision) is presented and investigated in detail, which allows the reconstruction of the 3D motion field from the image sequence obtained by a stereo camera system. Given correspondences of stereo measurements over time, this principle estimates the 3D position and the 3D motion vector of selected points using Kalman Filters, resulting in a real-time estimation of the observed motion field. To estimate the absolute motion field, the ego-motion of the moving observer must be known precisely. Thus, a novel algorithm to estimate the ego-motion from the image sequence is presented. As the 6D-Vision principle is not restricted to particular image processing algorithms, various optical ow and stereo algorithms are evaluated. In addition, two novel scene ow algorithms are introduced, measuring the optical ow and stereo information in a combined approach. This yields more precise and robust results. The application to real-world data, including a demonstrator vehicle for autonomous collision avoidance, is illustrated throughout the thesis.