MPEG 4 is a basic tool for interactivity and manipulation of video sequences. Video object segmentation is a key issue in defining the content of any video sequence, which is often divided into two steps: initial obj...MPEG 4 is a basic tool for interactivity and manipulation of video sequences. Video object segmentation is a key issue in defining the content of any video sequence, which is often divided into two steps: initial object segmentation and object tracking. In this paper, an initial object segmentation method for video object plane(VOP) generation using color information is proposed. Based on 3 by 3 linear templates, a cellular neural network (CNN) is used to implemented object segmentation. The Experimental results are presented to verify the efficiency and robustness of this approach.展开更多
Segmentation of semantic Video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic Segmentation of VOP's Based on...Segmentation of semantic Video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic Segmentation of VOP's Based on Spatio-Temporal Information (SBSTI) is proposed.The proceeding results demonstrate the good performance of the algorithm.展开更多
传统检测房室平面位移的方法因测量信息不完整及房室平面特征点跟踪不准等缺点,造成房室平面位移(Atrioventricular Plane Displacement,AVPD)曲线失真。利用图像处理技术结合心血管核磁共振图像(Cardiovascular Magnetic Resonance,CMR...传统检测房室平面位移的方法因测量信息不完整及房室平面特征点跟踪不准等缺点,造成房室平面位移(Atrioventricular Plane Displacement,AVPD)曲线失真。利用图像处理技术结合心血管核磁共振图像(Cardiovascular Magnetic Resonance,CMR)可以更准确地检测室平面位移。首先,采用具有通道和空间可靠性的判别相关滤波器(Discriminative Correlation Filter with Channel and Spatial Reliability,CSR-DCF)增强对房室平面特征点的跟踪能力。其次,基于心脏核磁共振图像的空间信息构建三维的房室平面多面体,从整体上评估房室平面位移。最后,通过主成分分析法(Principal Component Analysis,PCA)重建房室平面的位移曲线。实验表明,本文方法重建后的房室平面位移保留了原始数据信息的96%以上并且房室平面位移曲线更加平滑的同时符合生理特性。展开更多
文摘MPEG 4 is a basic tool for interactivity and manipulation of video sequences. Video object segmentation is a key issue in defining the content of any video sequence, which is often divided into two steps: initial object segmentation and object tracking. In this paper, an initial object segmentation method for video object plane(VOP) generation using color information is proposed. Based on 3 by 3 linear templates, a cellular neural network (CNN) is used to implemented object segmentation. The Experimental results are presented to verify the efficiency and robustness of this approach.
文摘Segmentation of semantic Video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic Segmentation of VOP's Based on Spatio-Temporal Information (SBSTI) is proposed.The proceeding results demonstrate the good performance of the algorithm.
文摘传统检测房室平面位移的方法因测量信息不完整及房室平面特征点跟踪不准等缺点,造成房室平面位移(Atrioventricular Plane Displacement,AVPD)曲线失真。利用图像处理技术结合心血管核磁共振图像(Cardiovascular Magnetic Resonance,CMR)可以更准确地检测室平面位移。首先,采用具有通道和空间可靠性的判别相关滤波器(Discriminative Correlation Filter with Channel and Spatial Reliability,CSR-DCF)增强对房室平面特征点的跟踪能力。其次,基于心脏核磁共振图像的空间信息构建三维的房室平面多面体,从整体上评估房室平面位移。最后,通过主成分分析法(Principal Component Analysis,PCA)重建房室平面的位移曲线。实验表明,本文方法重建后的房室平面位移保留了原始数据信息的96%以上并且房室平面位移曲线更加平滑的同时符合生理特性。
文摘提出一种新的摄像机标定方法,该方法基于2D共面参照物摄像机标定方法和傅里叶条纹分析方法.将已知相位分布的平面二维正弦灰度调制条纹图作为平面标定靶,通过傅里叶条纹分析方法计算出两个截断正交相位分布,利用截断正交相位分布并结合二维正弦条纹图特点提取相应的图像特征点,建立像素坐标与2D平面坐标的对应关系.将该二维平面靶在摄像机成像空间中放置不同的位置,并完成相应的特征点提取,根据2D共面参照物摄像机标定方法即可完成摄像机标定.该方法利用平面相位测量的高准确度来提高标定特征点的提取准确度,从而提高标定准确度.实验对双摄像机系统进行了标定,标定后该系统对标定靶进行测量,标准偏差达到0 .010 mm.
