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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 顏嗣鈞 | |
dc.contributor.author | Kai-Jun Wang | en |
dc.contributor.author | 王愷俊 | zh_TW |
dc.date.accessioned | 2021-06-16T23:16:47Z | - |
dc.date.available | 2015-08-15 | |
dc.date.copyright | 2012-08-15 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-08-01 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65035 | - |
dc.description.abstract | 行人辨識一直是物件辨識領域當中一個相當熱門的研究主題,由於交通意外事故一
直都是國內十大死因之一,因此,有越來越多的車廠願意將駕駛輔助系統搭載於自家的產品之上,以加強駕駛的安全性,其中包含車道辨識、車輛辨識、以及行人辨識都是相當重要的研究領域,使得駕駛人可以更安心上路。 駕駛輔助系統之人物辨識對於準確率以及即時性的要求相當高,因此,本論文提出 以兩個CCD 攝影機的雙眼立體視覺產生視差圖,根據視差圖之深度資訊劃分前景物與背景物,再利用障礙物於三維空間之物理特性切割出我們感興趣的區域,最後擷取出行人之梯度方向直方圖特徵,並經由支援向量機分類驗證行人影像,成功分類出行人影像後,我們可以更進一步的利用雙眼立體視覺當中的三角幾何關係計算出行人距離。經由實驗驗證,我們的方法可以達到更快速且正確的辨識結果,以及在距離估測上的準確性也有相當不錯的效果。 | zh_TW |
dc.description.abstract | Pedestrian detection is always a popular research topic in the objective detection area due to transportation accident is one of the main causes of death in Taiwan. Hence, more vehicle companies are willing to accompany driving assistance system in their own products in order to increase the safety of driving. In addition, lane detection, vehicle detection, and pedestrian detection are significant research fields to allow safer driving.
Accuracy rate and real time processing are highly required in the pedestrian detection of driving assistance system, therefore, our essay suggests to use two CCD camera to build stereo. Based on the depth information of stereo, we can divide foreground and background.Following, the obstacle of physical property of three-dimensional space are used to define and segment the region that we are interesting to capture the histogram of oriented gradient feature of pedestrian. Furthermore, through support vector machine classifier to verify the pedestrian image. Finally, we calculate the pedestrian distance by using the stereo of triangular geometric relations. According to our experiments, this method is able to achieve a faster and more correct classify result. As well as a remarkable result in accuracy of distance estimation. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T23:16:47Z (GMT). No. of bitstreams: 1 ntu-101-R99921075-1.pdf: 4632930 bytes, checksum: a5cf94cdbede3da26ef5b76f3742dcc4 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | 誌謝 ..................................................... I
摘要 .................................................... II ABSTRACT................................................ III 目錄 .................................................... IV 圖目錄................................................... VI 第1 章. 緒論 ............................................. 1 1.1 前言 ............................................... 1 1.2 研究動機與目的 ........................................ 1 1.3 相關研究 ............................................. 2 第2 章. 電腦視覺基本理論與攝影機校正 ......................... 6 2.1 攝影機校正原理 ........................................ 7 2.1.1 相機內部參數 ........................................ 9 2.1.2 相機外部參數 ....................................... 10 2.2 攝影機校正 ............................................12 2.2.1 內部參數的條件限制式 ................................. 13 2.2.2 求解內部參數 ....................................... 14 2.2.3 求解外部參數 ....................................... 15 2.2.4 求非線性最佳解 ...................................... 16 2.2.5 求畸變係數 ......................................... 16 第3 章. 雙眼立體視覺原理與視差圖 ............................ 18 3.1 雙眼立體視覺基本理論 ................................... 18 3.2 極線幾何 ............................................. 21 3.3 雙眼立體視覺標定(Stereo Calibration) .................. 23 3.4 雙眼立體視覺校正(Stereo Rectification)................. 25 3.5 對應點匹配(Stereo Correspondence) .................... 27 第4 章. 障礙物及行人候選區框選 .............................. 30 4.1 像差影像分層 ......................................... 30 4.2 連通影像分割 ......................................... 31 4.3 三維資訊條件限制....................................... 33 第5 章. 行人偵測 ......................................... 36 5.1 支援向量機 ........................................... 36 5.2 梯度方向直方圖(Histogram of Oriented Gradients,HOG)... 39 5.2.1 高斯濾波 .......................................... 40 5.2.2 梯度計算 .......................................... 40 5.2.3 特徵型態與定義....................................... 42 第6 章. 實驗結果 ......................................... 43 6.1 實驗環境配置 ......................................... 43 6.2 雙眼攝影機校正 ........................................ 44 6.3 對應點匹配實作與劃出障礙物 .............................. 47 6.4 行人辨識實驗 ......................................... 49 6.5 距離估測之準確度 ...................................... 53 6.6 不同場景實驗檢測結果 ................................... 55 第7 章. 結論與未來展望 .................................... 58 參考文獻 ................................................ 60 | |
dc.language.iso | zh-TW | |
dc.title | 利用雙眼立體視覺輔助行人偵測的方法 | zh_TW |
dc.title | A Pedestrian Detection Method Based on Binocular Stereo Vision | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 黃秋煌,郭斯彥,雷欽隆 | |
dc.subject.keyword | 雙眼視覺,行人辨識,支援向量機,梯度方向直方圖, | zh_TW |
dc.subject.keyword | stereo vision,pedestrian detection,support vector machine(SVM),histogram of oriented gradients(HOG), | en |
dc.relation.page | 62 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2012-08-01 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
顯示於系所單位: | 電機工程學系 |
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