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Surveillance video of the vehicle and pedestrian detection

Author: ZuoQing
Tutor: YangXiaoKang；XuZuo
School: Shanghai Jiaotong University
Course: Signal and Information Processing
Keywords: Vehicle , pedestrian detection Foreground detection Support Vector Machine
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 352
Quote: 2
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Abstract


Surveillance video of the vehicle and pedestrian detection, intelligent video processing is an important issue, because of its multi-disciplinary fusion technology, has broad market prospects and become a worldwide research institutions, corporate research and development priorities. However, in a variety of dynamic scenarios under different congestion levels, stable and accurate detection of a vehicle and pedestrian, is still difficult to achieve a good challenging topic. This article describes the prospects of detection methods and different environments vehicle, pedestrian detection methods research and development status, for different application environments presents different detection methods, and in the following aspects do some exploratory work: 1. To overcome existing prospects vulnerable scene detection algorithm dynamically change impacts, foreground segmentation is not accurate and complete problem, this paper based on Gaussian mixture model of the classic foreground detection algorithm based on the introduction of time consistency analysis simplifies computing, the use of spatial information to filter noise to regional growth prospects split manner, thereby inhibiting dynamic background interference, accurate object segmentation and retain a clear outline of the object. In addition, the color model and the local binary pattern cone are combined in a large area to achieve effective removal of the shadow of moving objects in the dark, while ensuring uninterrupted. (2) In order to make road monitoring video vehicle detection is no longer confined to specific shooting direction, specific area and the specific light environment constraints, this paper presents a more robust shape, corner points, lines and other geometric invariant features and SVM model features learning and training. By wavelet coefficients with the common characteristics and regional characteristics of local binary pattern, which demonstrates this feature in computation time and recognition performance superiority. 3 In order to solve the crowded pedestrian environment effectively with each other rapidly dividing difficult problem, this paper uses the hierarchy, the first comprehensive outlook profile and shape information for pedestrian orientation and scale of the basic initial estimate, and then use to complete the pedestrian HoG descriptors final confirmation. The method can also improve the speed and accuracy of pedestrian detection, in order to provide an accurate analysis of subsequent events object description. The reality of working in a variety of scenarios in a systematic surveillance video of the test, the results show that the proposed method can be better achieved under different circumstances vehicular and pedestrian detection. Meanwhile, the proposed method based event detection system, TrecVid1 2008 international event detection contest won best event detection result of the good results.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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