Full metadata record
DC FieldValueLanguage
dc.contributor.author戴玉書en_US
dc.contributor.authorDai, Yu-Shuen_US
dc.contributor.author王聖智en_US
dc.contributor.authorWang, Sheng-Jyhen_US
dc.date.accessioned2014-12-12T01:46:40Z-
dc.date.available2014-12-12T01:46:40Z-
dc.date.issued2011en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT079811656en_US
dc.identifier.urihttp://hdl.handle.net/11536/46821-
dc.description.abstract在本論文中,我們提出一套可以全天二十四小時運作的戶外停車 場空位偵測系統。特別針對夜晚的情況,我們設計出一種動態調整曝 光值的取像方式,能同時將多張不同曝光值的影像,經融合處理後得 到一張資訊較完整的融合影像。接著,藉由把整個停車場看成一種面 與面的結構組合、結合BHF 模型和3D 場景中車輛的幾何資訊、利 用以HOG 為基礎的擷取方式,我們擷取出融合影像內各個面相所對 應的特徵向量。最後,把每個面所擷取出的特徵向量以機率模型的方 式,分別比對出每種不同組合的停車假設,而與特徵內容最符合的假 設狀態即為我們的偵測結果。透過本系統,我們可以穩定的分析出停 車場的停車狀況,並提供停車場內空位的位置資訊。zh_TW
dc.description.abstractIn this thesis, we propose a vacant parking space detection system that works 24 hours a day. Especially, to capture images at night, we design a capture mode that takes images under different exposure settings and fuses these multi-exposure images into a clearer image. Besides, we combine a proposed Bayesian hierarchical framework (BHF) with the 3D-scene information by treating the whole parking lot as a structure consisting of plentiful surfaces. With the proposed framework, we extract feature vectors from each surface based on a modified version of the Histogram of Oriented Gradients (HOG) approach. By incorporating these feature vectors into specially designed probabilistic models, we can estimate the current parking status by finding the optimal statistical hypothesis among all possible status hypotheses. Experiments over real parking lot scenes have shown that our system can reliably detect vacant parking spaces day and night on an outdoor parking lot.en_US
dc.language.isoen_USen_US
dc.subject停車位zh_TW
dc.subjectparking spaceen_US
dc.title以視覺為基礎之戶外全天停車場空位偵測系統zh_TW
dc.titleA Vision-based Vacant Parking Space Detection Framework for All-Day Outdoor Parking Lot Managementen_US
dc.typeThesisen_US
dc.contributor.department電子研究所zh_TW
Appears in Collections:Thesis


Files in This Item:

  1. 165601.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.