- 學位論文
十字路口行人與車輛之追蹤及分類
Tracking and Classification for Pedestrians and Cars at Crossing
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摘要
由於現代社會的交通日趨繁忙，智慧型運輸系統(ITS, Intelligent Transportation System)的建置已經變成一個相當重要的課題。如何能夠自動偵測出道路上的行人與車輛，並且進一步加以分類或追蹤，更是智慧型運輸系統中相當重要的一環。本論文即在提出一套能夠自動偵測、追蹤、並分類路口行人與車輛的交通監控系統。 本論文提出的方法內容簡述如下。在影像前置處理部份，本研究提出一種自動物體外型擷取演算法。首先架設攝影機以擷取路面交通影像，並使用所提之建立淨空背景方法作為分析移動物體之用。再將攝影機所拍攝的影像以影像相減為基礎，搭配多種影像處理的技術，把畫面中移動的物體外型輪廓從背景之中抽離出來。下一步是物體追蹤部份，利用主動輪廓模型(Active Contour Model)可以不斷包圍非剛性物體的特性，對各個移動的物體進行持續的追蹤。接著是物體辨識部份，經由預先設定的特徵分類法則，對畫面中各個移動的物體進行特徵的比對，分辨其為行人或者車輛。最後由實驗結果驗證本論文所提出之方法是可行的。
並列摘要
This study proposes a traffic surveillance system which can automatically detect, track, and classify pedestrians and cars at crossing. Following is a simple description of the proposed method. An automatic moving object segmentation algorithm is proposed in image pre-process step. At this step, a camera is used to capture the video at crossing, and a clear background is built by the proposed method for moving objects detection. The shape and contour of moving objects in the image are extracted by background subtraction and multiple image process techniques. Next is the object tracking step. Considering its deformable characteristic, the active contour model is applied to continuously track each moving object, even it is non-rigid. Following is the object classification step; multiple features are used to determine whether a moving object is a pedestrian or car. Finally, the proposed method is verified through experiments to be practicable.
參考文獻
[3] Nelson H.C. Yung, Andrew H.S. Lai, “An Effective Video Analysis Method for Detecting Red Light Runners”, IEEE Transactions on Vehicular Technology, Vol. 50, No. 4, pp. 1074-1084, July 2001.
[5] O. Masoud, Nikolaos P. Papanikolopoulos, “A Novel Method for Tracking and Counting Pedestrians in Real-Time Using a Single Camera”, IEEE Transactions on Vehicular Technology, Vol. 50, No. 5, pp. 1267-1278, Sep. 2001.
[6] 白家榮，陳世旺，「十字路口行人的偵測及追蹤」，國立台灣師範大學資訊教育研究所，碩士論文，中華民國九十一年六月。
[9] M. Kass, A. Within, D. Terzopoulos, “Snakes: Active Contour Models”, International Journal of Computer Vision, Vol. 1, pp. 321-331, 1988.
[11] N. Peterfreund, “Robust Tracking of Position and Velocity With Kalman Snakes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, No. 6, pp. 564-569, Jun. 1999.