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摘要


The research in the robot vision becomes more and more attractive since the demand for robot is growing. To detect and avoid the obstacles in the outdoor environment is an important task for a moving robot. In this paper, we propose a real-time detection of the obstacle based on the computer vision with single camera. The dense optical flow method is adopted to extract the training data for a classifier model using support vector machine (SVM). The speeded-up robust features method is used to detect the interest points to be verified as the obstacle points or not by a SVM classifier. Moreover, a measurement of the spatial weighted saliency map is proposed to highlight the pixels of the obstacle. Finally, the obstacle points and the saliency map are combined to locate the region of the obstacle. The experimental results show that the proposed algorithm can effectively detect the obstacle in the outdoor environment.

關鍵字

obstacle detection optical flow saliency SURF SVM

被引用紀錄


黃俊瑋(2008)。以影像為基礎之量測方法及其在平面定位之研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2008.01204
吳欣倫(2012)。整合動靜態視覺資訊的前車停止與啟動偵測〔碩士論文,國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-1903201314443291
陳羿霖(2013)。基於立體視覺影像分析之先進汽車駕駛安全輔助技術〔碩士論文,國立中正大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0033-2110201613563588

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