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  • 學位論文

適用於物體追蹤一維時空域濾波器之設計與應用

Tracking Moving Objects in Image Sequences Using 1-D Tajectory Filters

指導教授 : 貝蘇章

摘要


在過去的十年中,多媒體的科技技術有很重大的進步與發展。 在各方面都逐漸走向數位化。從靜態的影像處理技術到影像序列,開拓了一個新的領域。因此影像序列處理技術是時空域信號處理的一個重要工具。 這篇論文的第一部份,重點放在影像序列的物體追蹤。首先,我們先介紹這一類的信號特性及頻率響應。有了這些資訊後,就能知道如何去設計物體追蹤濾波器。 接著,我們提出一個在時空域裡的一階IIR濾波器來做物體追蹤。此方法與其他用多維濾波器來追蹤物體的方法不一樣,不需要傅式轉換,完全在時空域實行。為一個能簡單設計,並且低計算複雜度的方法。不論物體軌跡是線性或是非線性,都能成功的提取出來。實驗結果可以看出成果是良好的,而且能實際即時施行。 在第二部份,將整理介紹擁有好的偵測能力的餘弦系列窗。只要在視窗裡加上可指定位置的附葉窪溝和達到高的附葉衰減率,此視窗就能把在強信號附近的弱信號偵察出來。並且強度也能夠準確的測出。此類的視窗函數可以讓使用者自行設計所需要的視窗,以達到最好的分析效果。

並列摘要


In the past decade or so, there have been magnetic developments in multimedia technologies. It has become very clear that that all aspects of media are digitized. Extending image processing from static individual images to image sequences opens up a new world of information. Image sequence processing is becoming a tremendous tool to analysis spatio-temporal data in all areas. In part 1 of this thesis, we will focus on tracking the moving objects in the image sequence. First, the properties of this kind of signals and its frequency responses will be introduced. With this information in hand, the structure of the filter that can extract the moving object is known. Furthermore, we will propose a 1-D IIR filter in spatio-temporal domain for object tracking. Different from other multi-dimensional filter design methods for object tracking, it is easy to design and can be implemented without Fourier transform causing low computational complexity. The 1-D trajectory filter can be used to track the objects moving with linear or nonlinear trajectory without the prior knowledge of trajectories. The experimental results show that its performance is satisfactory and useful for real time practical applications. In part 2, the cosine series windows with good detectability are introduced. By adding steerable sidelobe dips and achieving high sidelobe falloff rate, the windows can be used to detect a weak signal with a strong signal nearby. Furthermore, the amplitudes of the signals are also accurately estimated. These windows can be easy to design.

參考文獻


Chapter 1
[1.1] Adelson, E. H. and Bergen, J. R., “Saptio-temporal Energy Mod els for the Perception of Motion”, Journal of Optical Society of America(J.O.S.A.), pp. 284-299, Feb. 1985.
[1.2] Porat B., and Friedlander B., “A Frequency Domain Algorithm for Multiframe Detection and Estimation of Dim Targets”, IEEE Conference on Computer Vision, pp. 591-594, 1987.
[2.1] Porat, B., and Friedlander B., “A Frequency Domain Algorithm for Multiframe Detection and Estimation of Dim Targets”, Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 12, Issue 4, pp.398-401, Apr. 1990.
[2.4] Bruton, L.T. and Bartley, N.R., “Highly selective three-dimensional recursive beam filters using intersecting resonant planes,” IEEE Trans. Circuits and Systems, Vol. CAS-30, No. 3, pp. 190-193, March 1983

被引用紀錄


林于翔(2009)。影像處理技術於多型態路口交通參數之擷取研究〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2009.10282

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