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Student Number 975202091
Author Lan-Yi Kang(藍易康)
Author's Email Address No Public.
Statistics This thesis had been viewed 559 times. Download 111 times.
Department Computer Science and Information Engineering
Year 2009
Semester 2
Degree Master
Type of Document Master's Thesis
Language zh-TW.Big5 Chinese
Title Stop-and-go and Top-view Obstacle Detection based on Dynamic Vision
Date of Defense 2010-07-07
Page Count 98
Keyword
  • stop-and-go
  • Top-view
  • Abstract It is inconvenience and danger while driving in urban areas. Drivers spend much time waiting for traffic signals and stuck in jams. Lack of concentration at such moments may lead to accidents. Due to the limitation of field of view, drivers are mostly unable to see all the area around the vehicle during driving. For the safety of drivers, the stop-and-go and top-view obstacle detection methods are proposed in this study. Corners are used as features to calculate optical flow. We perform stop-and-go and top-view obstacle detections based on the optical flow.
    In the stop-and-go detection method, we first filter optical flow and adjust the length of optical flow. The length of optical flows of an object is almost the same. The adjusted length is used as the condition for clustering. Then, we use these moving objects to recognize whether the front vehicle is stopping or going. This detection method can also avoid the effects of vehicles in different direction, variant weather, and the light at nighttime.
    In the top-view obstacle detection method, the direction, position, and length of optical flows are used as condition for clustering. By analyzing the trajectory of moving objects and computing the possible collision time, we can recognize whether the moving object is dangerous.
    The proposed methods are evaluated in several variant environments. The detection rate of stop-and-go method is 99? and the frame rate is 25 frames per second. The detection rate of the top-view detection method is 98? and the frame rate is 30 frames per second.
    Table of Content 摘要ii
    Abstractiii
    誌謝iv
    目錄v
    圖目錄vii
    表目錄xi
    第一章 緒論1
    1.1 研究動機1
    1.2 系統架構2
    1.3 論文架構4
    第二章 相關研究6
    2.1 前車停止與啟動偵測6
    2.2 俯瞰偵測9
    2.3 角點偵測12
    2.4 光流向量估計16
    第三章 特徵擷取與光流向量估計21
    3.1 角點偵測21
    3.2 計算光流向量23
    第四章 前車停止啟動偵測27
    4.1 光流向量篩選與調整27
    4.1.1 光流向量篩選28
    4.1.2 光流向量調整31
    4.2 光流向量分群36
    4.2.1 以相鄰向量比較相似性為基礎的分群36
    4.2.2 簡單群聚搜尋方法分群38
    4.3 前車啟動停止判斷39
    4.3.1 以角度基礎的判斷方法39
    4.3.2 以調整後向量大小為基礎的判斷方法41
    第五章 俯瞰碰撞偵測43
    5.1 光流向量篩選與分群43
    5.2 俯瞰碰撞偵測44
    5.2.1 固定範圍偵測44
    5.2.2 劃分區域偵測45
    第六章 實驗結果52
    6.1 實驗環境52
    6.2 前車停止與啟動偵測結果53
    6.2.1 前車停止偵測53
    6.2.2 前車啟動偵測61
    6.2.3 分群方法結果比較68
    6.2.4 判斷準則方法結果比較70
    6.3俯瞰碰撞偵測結果71
    6.3.1 固定範圍偵測71
    6.3.2 劃分區域偵測73
    6.4實驗平台與效能77
    第七章 結論與未來展望79
    7.1 結論79
    7.2 未來展望80
    參考文獻81
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    Advisor
  • Din-Chang Tseng(曾定章)
  • Files
  • 975202091.pdf
  • approve in 2 years
    Date of Submission 2010-07-27

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