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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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🏛️國立陽明交通大學機構典藏

Subject: search.filters.subject.Pattern recognition

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Now showing 1 - 10 of 12
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    2D Histogram-based player localization in broadcast volleyball videos
    (2016-06)
    Hsu, Chun-Chieh
    ;
    Chen, Hua-Tsung
    ;
    Chou, Chien-Li
    ;
    Lee, Suh-Yin
    ;
    資訊工程學系
    Player location is one of the most informative cues for obtaining tactics arrangement and collecting descriptive game statistics. However, state-of-the-art supervised learning-based methods for player localization require a large amount of labeled training data. Hence, the development of automatic systems for player localization becomes indispensable. Volleyball games reach a huge audience base and contain a variety of tactical strategies, necessitating the implementation of systems for inferring tactics and analyzing formations automatically. Therefore, a novel 2D histogram-based player localization method capable of locating players with occlusions is developed and presented in this paper. The proposed system is able to automatically detect the court lines for camera calibration, extract players by calculating both x and y histograms of extracted player masks, and visualize the team formations on real-world court model. The experiments on broadcast volleyball videos demonstrate efficient and effective results against a traditional object segmentation method (connected component analysis) and a supervised learning approach utilizing histogram of oriented gradient features.
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    規劃最佳避碰路徑---研究及系統發展(II)
    (1993)
    莊仁輝
    ;
    JEN-HUICHUANG
    ;
    交通大學資訊科學研究所
    本計畫為上年度「規劃最佳避碰路徑--研究及 系統發展」之延伸,目的在探討最佳避碰路徑之 規劃.其研究著重於經由排斥場的建立而賦與所 規劃路徑之避碰特性.傳統的避碰通常利用檢查 或控制物體間少數最近點的距離而達成.在物體改變相對位置時,上述最近點位置之變化並不平 滑,而其相對應之避碰路徑亦然,排斥場利用物體 表面的許多點理論上所有點來計算碰撞發生之可 能性,因而沒有上述的問題.上年度的計畫中,我們 完成了三年空間排斥場的理論分析並將其結果成 功的應用於三度空間物體之骨架抽取上.在系統 發展方面,我們完成了具備圖形式人機介面的規 劃系統的雛型.此系統並已被用圖形識別中物體 形狀之比對而有初步的結果.本計畫除了將就上 述結果作更深入的研究外,並將進一步探討避碰 場更廣泛的應用在其他領域的可能性.具體的例 子包括三度空間路徑之規劃與機械手臂運動之規 劃.本計畫所發展之規劃系統將提供一解決實際 幾何問題的多用途工具.將來,可望以此系統為核 心結合其他影像處理技術,發展成一可接收並處 理更廣泛資訊(如聲波,紅外線,光學影像等)的系 統而應用於自動車,無人太空探測及機器人等方 面.
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    光學神經網路與圖像辨識前置處理器之研究
    (1994)
    許根玉
    ;
    HSU KEN-YUH
    ;
    國立交通大學光電工程研究所
    這個計畫是由國立交通大學光學計算實驗 室與德國Erlangen大學應用光學系共同合作的研 究計畫,其內容是關於用光學方法實現的一種 圖像辨認之前置處理器,以及其與光學神經網 路構成之圖形辨識系統之研究.其主要目標是 融合光學平行計算之優點及神經網路容錯之韌 性,以發展具有平移□旋轉及大小不變性之光 學影像辨識系統.這個計畫之工作重點有下列 三項:(1)以電腦模擬吾人所推導之影像前置處理法則,研究其潛力及限制.(2)以光學技術實現 前置處理法測.(3)將光學前置處理器與吾人所 研究之光學穿梭神經網路配合構成影像辨識系 統.以上諸項研究乃是我們在光學神經網路之 合作基礎上更深入之研究,其成果將對光學影 像辨認技術有重要項獻.
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    電腦系統中心---電腦視覺技術與應用---總計畫
    (1995)
    陳稔
    ;
    CHEN ZEN
    ;
    國立交通大學資訊工程研究所
    本整合型計畫目的在於利用影像處理、圖 形識別、投影幾何學、人工智慧等多種理論為 基礎,分析光源、物體、相機三者之間成像關 係,以由二維影像資料,推導物體與相機之間相 對空間位置關係.本總畫下分三個子計畫,分別 由不同層面來研究電腦視覺技術,計光源方面 採用可見光(子計畫一、二)及雷射光(子計畫三 ),光源投射分均勻光源(子計畫一、二)及平結 行結構光(子計畫三)、相機組合分單一相機(子 計畫一、三)及雙眼相機(子計畫二),拍攝對象 分靜止物體(子計畫一、三)及運動物體(子計畫 二),研究技術項目分相機定位(子計畫一),運動 追蹤(子計畫二),物體尺寸量測(子計畫三).三者 之間相通之處是(1)研究各別環境下物體本身與 成像影像中特徵點或線對應關係之推導;(2)可 見光或雷射結構光可處理的資料的互補性;(3) 單長影像分析與多張影像分析之不同之處及其 可互用之地方.
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    電腦視覺技術與應用---總計畫(II)
    (1996)
    陳稔
    ;
    國立交通大學資訊工程學系
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    可靠之基頻軌跡偵測及聲調辨認之研究
    (2001)
    王逸如
    ;
    WANG YIH-RU
    ;
    交通大學電信工程系
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    以形狀辨識為基礎的診斷訓練輔助對時間壓力下失效偵測與診斷之影響
    (2001)
    許尚華
    ;
    SHANG HWAHSU
    ;
    國立交通大學工業工程與管理學系
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    先進中文語音辨認系統之發展(II)
    (2001)
    陳信宏
    ;
    CHEN SIN-HORNG
    ;
    交通大學電信工程系
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    Recognizing jump patterns with physics-based validation in human moving trajectory
    (2013-10-01)
    Chen, Hua-Tsung
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    Ma, Kuo-Lian
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    Chuang, Jen-Hui
    ;
    Lin, Horng-Horng
    ;
    資訊工程學系
    This paper presents an approach to recognize jump patterns in human moving trajectory, differentiating jump tracks from planar moving tracks. Since human moving trajectory is one of the most informative representations for content understanding and event detection, trajectory-based video analysis has been gaining popularity. However, a jump action typically leads to violent change in human moving trajectory, since the person suddenly leaves the original plane on which he/she has been moving. The abnormal tracks of the trajectory would influence the performance of trajectory-based video analysis. Hence, differentiating jump tracks from planar moving tracks is of vital importance, not to mention that jump actions typically imply significant events, especially in sports games. In this paper, volleyball videos are used as case study to demonstrate the effectiveness of our proposed jump pattern recognition approach. We derive player trajectory by head tracking, analyze the movement of each player, and recognize potential jump tracks in player trajectories based on two important characteristics: (1) jumps cause pulse-like tracks in the trajectory and (2) the extensions of such tracks go through the vanishing point of vertical lines in the scenes. Finally, the jump positions/heights are estimated, in addition to the planar moving trajectory of each player on the court ground. The experiments show that satisfactory results can be obtained with the proposed recognition scheme. (C) 2013 Elsevier Inc. All rights reserved.
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    HMM-based ball hitting event exploration system for broadcast baseball video
    (2012-07-01)
    Chen, Hua-Tsung
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    Chou, Chien-Li
    ;
    Tsai, Wei-Chin
    ;
    Lee, Suh-Yin
    ;
    Lin, Bao-Shuh P.
    With the dramatic growth of fandom population, a considerable amount of research efforts have been devoted to baseball video processing. However, little work focuses on the detailed follow-ups of ball hitting events. This paper proposes a HMM-based ball hitting event exploration system for broadcast baseball video. Utilizing the strictly-defined layout of the baseball field, the proposed system first detects the game-specific spatial patterns in the field, such as the field lines, the bases, the pitch mound, etc. Then, the play region the currently camera-focused region of the baseball field is identified for frame type classification. Since the temporal patterns of presenting the game progress follow a prototypical order, we consider the classified frame types as observation symbols and recognize ball hitting events using HMM. Experiments conducted on broadcast baseball video show encouraging results in frame type classification and ball hitting event recognition. Three practical applications, including highlight clip extraction by user-designated query, storyboard construction, and similar event retrieval, are introduced to address the applicability of our system. (C) 2012 Elsevier Inc. All rights reserved.