| 英文摘要 | This thesis focuses on the researches of pedestrian detection and tracking on the mobile platform, which are the key technologies in the Pedestrian Protection Systems (PPSs). PPSs strive to build up an independent and intelligent driver-assistant system for pedestrian detection and tracking. These technologies can enhance the safety of driving, and have applicative signification for protecting the pedestrian’s life.On the other hand, the technologies applied in PPSs refer to many research areas, such as sensors, automatic control, artificial intelligence, pattern recognition, information in- tegration and so on. They are research interests of cross-disciplines, and are also the evaluation platform of the theory from these areas, with high academic signification. Compared with general object detection and tracking, the pedestrian detection and tracking on mobile platform has its own characteristics due to its application, which includes 1) the dynamic of application environment, 2) the wide range of application, 3) real-time processing requirement and 4) the succinct procedure of the algorithm program. Focusing on these problems and challenges, this thesis makes deep research on the pedestrian detection and tracking algorithm for mobile vision platform. First, from the view of extracting intrinsic feature, this thesis introduces context feature to be a good description to represent the pedestrian appearance which is a nonrigid target. A feature extraction method is improved, and a new feature extraction method is also proposed for pedestrian detection. Moreover, we consider the movement continuity is a key characteristic of pedestrian tracking. An intrinsic feature with movement continuity preserving is extracted for pedestrian tracking based on manifold learning. Then, from the view of feature model, we introduce the hierarchical classifier model with multi-templates of target postures for pedestrian detection, which can re- duce the computational complexity. We also learn a generative model of intrinsic pedestrian manifold based on manifold learning. The pedestrian tracking can be real- ized in the intrinsic but low-dimensional space. At last, from the view of detection and tracking framework, we use neighbor search, Bayesian theory and so on to evaluate the effectiveness of these algorithms. Meanwhile, we proposed the preprocessing mechanism for foreground segmentation, bi-direction mapping and so on to improve the robustness of the algorithms, in w... |
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