Vehicle surrounding monitoring using weighted feature point matching
碩士 === 國立交通大學 === 電控工程研究所 === 100 === The number of traffic accidents is growing up quickly according to the research numbers in every year. Among of all the traffic accidents between vehicle and other generalized obstacles occur most frequently. Therefore, the number of high safety vehicles is in...
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ndltd-TW-100NCTU54490062015-10-13T20:37:27Z http://ndltd.ncl.edu.tw/handle/25474740937833092465 Vehicle surrounding monitoring using weighted feature point matching 利用權重式特徵點比對的車輛周遭監控系統 方奎理 碩士 國立交通大學 電控工程研究所 100 The number of traffic accidents is growing up quickly according to the research numbers in every year. Among of all the traffic accidents between vehicle and other generalized obstacles occur most frequently. Therefore, the number of high safety vehicles is increasing over the world. Many researchers proposed various pre-warning collision systems. However, the multi-system will confuse drivers on switching different systems. Hence, this study proposes a pre-warning system and integrates different system. We construct a vehicle surrounding monitoring system through four cameras and integrate an obstacle detection system on the vehicle surrounding monitoring system. In order to decrease the influence caused by ground texture. We also propose a new ground estimation technique to reduce the false alarm rate of obstacle detection. To evaluate the estimation result, we generate a ground truth table by manual to calculate the estimation error. Compared to other paper, our approach promotes the accuracy of ground movement estimation further to reduce the false alarm caused by ground texture. In this thesis, we integrate two systems to decrease the hardware cost and propose a novel ground movement estimation method to reduce the false alarm effectively. By detecting the object significantly arise the road plane, we realize vehicle pre-collision warning system. 林進燈 2011 學位論文 ; thesis 55 zh-TW |
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碩士 === 國立交通大學 === 電控工程研究所 === 100 === The number of traffic accidents is growing up quickly according to the research numbers in every year. Among of all the traffic accidents between vehicle and other generalized obstacles occur most frequently. Therefore, the number of high safety vehicles is increasing over the world. Many researchers proposed various pre-warning collision systems. However, the multi-system will confuse drivers on switching different systems. Hence, this study proposes
a pre-warning system and integrates different system. We construct a vehicle surrounding monitoring system through four cameras and integrate an obstacle detection system on the vehicle surrounding monitoring system. In order to decrease the influence caused by ground texture. We also propose a new ground estimation technique to reduce the false alarm rate of obstacle detection. To evaluate the estimation result, we generate a ground truth table by
manual to calculate the estimation error. Compared to other paper, our approach promotes the accuracy of ground movement estimation further to reduce the false alarm caused by ground texture. In this thesis, we integrate two systems to decrease the hardware cost and propose a novel ground movement estimation method to reduce the false alarm effectively. By detecting the object significantly arise the road plane, we realize vehicle pre-collision warning system.
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林進燈 |
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林進燈 方奎理 |
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方奎理 |
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方奎理 Vehicle surrounding monitoring using weighted feature point matching |
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方奎理 |
title |
Vehicle surrounding monitoring using weighted feature point matching |
title_short |
Vehicle surrounding monitoring using weighted feature point matching |
title_full |
Vehicle surrounding monitoring using weighted feature point matching |
title_fullStr |
Vehicle surrounding monitoring using weighted feature point matching |
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Vehicle surrounding monitoring using weighted feature point matching |
title_sort |
vehicle surrounding monitoring using weighted feature point matching |
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2011 |
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http://ndltd.ncl.edu.tw/handle/25474740937833092465 |
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AT fāngkuílǐ vehiclesurroundingmonitoringusingweightedfeaturepointmatching AT fāngkuílǐ lìyòngquánzhòngshìtèzhēngdiǎnbǐduìdechēliàngzhōuzāojiānkòngxìtǒng |
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