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    Title: 以影像基礎特徵進行物件追蹤;Object Tracking Using Low Level Image Features
    Authors: 陳冠維;Chen, Kuan-Wei
    Contributors: 電機工程研究所
    Keywords: 再追蹤;基礎影像特徵;物件追蹤;適應物件變形;Re-tracking;Low Level Image Features;Object Tracking;Adapt Object Deformation
    Date: 2016
    Issue Date: 2019-07-17
    Publisher: 電機工程研究所
    Abstract: 物件追蹤在電腦視覺領域是一個重要的研究,目的是在連續的影像中,不間斷地追蹤使用者有興趣的、特定的物件。本論文嘗試以影像基礎特徵進行物件追蹤的物件追蹤演算法,主要是利用針對每一個物件本身都會存在特徵點,在影像中選取要追蹤的物件之後紀錄特徵點的資訊,並將兩兩相鄰的影像中的特徵點匹配,以此不斷追蹤物件,並在被追蹤的物件離開影像範圍或是被遮住之後取消追蹤,並用記錄的特徵點資訊不斷在影像中重新搜尋欲追蹤的物件,當物件重新出現時繼續追蹤。實驗結果證明提出的演算法可以有效的即時追蹤物件,並能適應物件的變形,以及實現物件的再追蹤。
    Object tracking is an important research field in computer vision in that it continuously identifies and records objects of interest in video frames. This thesis attempts to do object tracking using only low-level image features. The basic idea is to employ the low-level features to compose the so-called singular points, and to use these singular points as the basis for matching the object of interest in adjacent image frames. We demonstrate that if the tracking region surrounding the object of interest is well defined and maintained, the proposed method can provide effective tracking even under the conditions of minor obscurity, deformation, and re-entry.
    Appears in Collections:[Department of Electrical Engineering] thesis

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