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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/88085


    Title: 基於低運算複雜度範圍樹之感興趣物件檢索技術應用於影片摘要系統
    Other Titles: An efficient region of interest retrieval technique based on low-complexity range tree for video synopsis system
    Authors: 謝吉芳;Hsieh, Chi-Fang
    Contributors: 淡江大學電機工程學系碩士班
    江正雄;Chiang, Jen-Shiun
    Keywords: 物件偵測;物件辨識;影片檢索系統;K-D樹;Object detection;Object Tracking;video retrieval system;low-complexity
    Date: 2013
    Issue Date: 2013-04-13 12:00:05 (UTC+8)
    Abstract: 隨著近年攝影機的發展,使得數位化及高解析度的監視系統日漸普及,也對保全系統造成革命性的衝擊,根據研究報告指出,在英國有四百多萬的監視攝影機分布於城市街道,人們可以藉由將攝影機擺在關鍵的地點,藉此對該區域做日以繼夜的監控。因此,數位監視攝影系統在現今的保全上扮演著愈來愈重要的角色,越來越多的監視攝影機被配置於各種場合以確保人員及財產的安全。然而,大量的數位監視攝影資訊管理並不容易,需要花費大量的人力來監視監控畫面,負責監視監控畫面的人員在長時間專注盯著螢幕的情況之下也會造成的體力與精神的衰減與考驗,往往導致安全維護效率的降低。
    在本論文中,我們提出一個高效率的影片檢索系統,透過此系統,使用者感興趣的物件(Region of Interest, ROI)可以藉由電腦視覺中的物件偵測與物件辨識在長時間的影片中快速且有效率的被擷取出來,並且快速得索引與瀏覽。其利用了高斯混合模型(Gaussian Mixture Model, GMM)作為物件偵測的方法,為了讓使用者有效率的找出符合搜尋條件的物件,本文提出低複雜度範圍樹(Range Tree)來做為搜索的方法,其透過影片摘要(Video Abstraction)的技術,搜索到的物件將在短時間中播放,藉此達到快速檢索與瀏覽進而節省時間的目的。透過本系統,前處理物件擷取的部分FPS可以達到32,而搜索的的部分,時間複雜度則是從O(N)下降為O(logD-1N)。
    With the development of surveillance, digital and high resolution surveillance become more and more popular, impacting security system. It is reported that in the UK alone there are 4.2 million security cameras covering city streets. More and more digital surveillances are placed in everywhere for safety and security. Therefore digital surveillance system plays indispensable role in security today. However, the great amount of video captured form digital surveillance is difficult to manage and retrieve.
    In this study, we propose an efficient video retrieval technique. With the system, the Region of Interest (ROI) could be extracted in long video effectively and user could browse it with quick and easy way. According to the characteristic of the object in foreground distribution for the real-world video sequence, this work employs Gaussian Mixture Model (GMM) is used for object detection. In order to let users, a new video synopsis search approach, low-complexity rang tree algorithm, is proposed to improve the search the objects matching the conditions effectively in this work. With the time and space redundancy-reducing technique of video synopsis, the objects searched by users could be display in very short time. Therefore wanted objects and events could be found out and displayed quickly without wasting time watching the part without ROI. For the test video sequences, it can have an accuracy rate of 95% and achieve 32 Frame Per Second (FPS) of online phase in processing speed and time complexity of searching decrease from O(N) to O(logD-1N).
    Appears in Collections:[電機工程學系暨研究所] 學位論文

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