传统的机器视觉采用二维RGB图像,难以满足三维视觉检测的要求,深度图像能直接反映物体表面的三维特征,正逐渐受到重视。该文提出的方案将RGB和深度信息相结合,分割出物体所在区域,并利用梯度方向直方图(HOG,histograms of oriented grad...传统的机器视觉采用二维RGB图像,难以满足三维视觉检测的要求,深度图像能直接反映物体表面的三维特征,正逐渐受到重视。该文提出的方案将RGB和深度信息相结合,分割出物体所在区域,并利用梯度方向直方图(HOG,histograms of oriented gradients)分别提取RGB图像和深度图像特征信息。在分类算法上,该文采用k最邻近节点算法(k-NN)对特征进行筛选,识别出目标物体。试验结果表明,综合利用深度信息和RGB信息,识别准确率很高,此方案能够对物体和手势进行很好识别。展开更多
This paper presents a full-scale solution to the detection of the traffic data using laser device.Range images,gathered by a particular laser camera,are used in the multi-threshold segmentation.The multi-threshold seg...This paper presents a full-scale solution to the detection of the traffic data using laser device.Range images,gathered by a particular laser camera,are used in the multi-threshold segmentation.The multi-threshold segmentation is based on the height of the moving objects.In order to get the precise height of the moving objects,mapping of the original terrain is performed on the first step.On each layer,the clustering algorithm called iteration-self organizing data analysis techniques algorithm(ISODATA) is conducted afterwards.Kalman filtering technique is applied to recognize and track the moving objects.Extensive experiments show that these algorithms are effective in object recognition and tracking,as well as robust in the applications.展开更多
文摘传统的机器视觉采用二维RGB图像,难以满足三维视觉检测的要求,深度图像能直接反映物体表面的三维特征,正逐渐受到重视。该文提出的方案将RGB和深度信息相结合,分割出物体所在区域,并利用梯度方向直方图(HOG,histograms of oriented gradients)分别提取RGB图像和深度图像特征信息。在分类算法上,该文采用k最邻近节点算法(k-NN)对特征进行筛选,识别出目标物体。试验结果表明,综合利用深度信息和RGB信息,识别准确率很高,此方案能够对物体和手势进行很好识别。
基金the National Key Science and Technique Support Program of China during the Period of the 11th Five-Year Plan(No.2006BAJ18B02)
文摘This paper presents a full-scale solution to the detection of the traffic data using laser device.Range images,gathered by a particular laser camera,are used in the multi-threshold segmentation.The multi-threshold segmentation is based on the height of the moving objects.In order to get the precise height of the moving objects,mapping of the original terrain is performed on the first step.On each layer,the clustering algorithm called iteration-self organizing data analysis techniques algorithm(ISODATA) is conducted afterwards.Kalman filtering technique is applied to recognize and track the moving objects.Extensive experiments show that these algorithms are effective in object recognition and tracking,as well as robust in the applications.
