Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Real-time pose classification for driver monitoring
Driver pose estimation is one of the key components for future driver assistance systems since driver pose contains much information about his driving condition such as attention and fatigue levels. To this goal, a system is presented that detects the pose of the driver face in real time under realistic lighting conditions. The goal of the work is to automate the training phase, thereby eliminating the process of entering user information as much as possible. Two learning methods are presented for driver pose estimation. The first method uses unsupervised learning with Kohonen competitive networks, while the second method explores SVR with an appearance-based method.
Real-time pose classification for driver monitoring
Driver pose estimation is one of the key components for future driver assistance systems since driver pose contains much information about his driving condition such as attention and fatigue levels. To this goal, a system is presented that detects the pose of the driver face in real time under realistic lighting conditions. The goal of the work is to automate the training phase, thereby eliminating the process of entering user information as much as possible. Two learning methods are presented for driver pose estimation. The first method uses unsupervised learning with Kohonen competitive networks, while the second method explores SVR with an appearance-based method.
Real-time pose classification for driver monitoring
Xia Liu, (Autor:in) / Youding Zhu, (Autor:in) / Fujimura, K. (Autor:in)
01.01.2002
451709 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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