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公开(公告)号：US20120308114A1
公开(公告)日：2012-12-06
申请号：US13118959
申请日：2011-05-31
IPC分类号： G06K9/00
CPC分类号： G05D1/0253 , G05D1/0251 , G05D2201/0213 , G06T7/285
摘要： Methods and systems for egomotion estimation (e.g. of a vehicle) from visual inputs of a stereo pair of video cameras are described. 3D egomotion estimation is a six degrees of freedom problem in general. In embodiments of the present invention, this is simplified to four dimensions and further decomposed to two two-dimensional sub-solutions. The decomposition allows use of a voting strategy that identifies the most probable solution. An input is a set of image correspondences between two temporally consecutive stereo pairs, i.e. feature points do not need to be tracked over time. The experiments show that even if a trajectory is put together as a simple concatenation of frame-to-frame increments, the results are reliable and precise.
摘要翻译： 描述了从立体声视频摄像机的视觉输入中进行自动运动估计（例如车辆）的方法和系统。 一般来说，3D自由度估计是一个六自由度问题。 在本发明的实施例中，将其简化为四维并进一步分解为两个二维子解。 分解允许使用表示最可能解决方案的投票策略。 输入是两个时间上连续的立体声对之间的一组图像对应，即不需要随时间跟踪特征点。 实验表明，即使轨迹作为帧到帧增量的简单串联组合在一起，结果是可靠和准确的。
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公开(公告)号：US08744169B2
公开(公告)日：2014-06-03
申请号：US13118959
申请日：2011-05-31
申请人： Gabriel Othmezouri , Ichiro Sakata , Jiri Matas , {hacek over (S)}t{hacek over (e)}pán Obdr{hacek over (z)}álek
发明人： Gabriel Othmezouri , Ichiro Sakata , Jiri Matas , {hacek over (S)}t{hacek over (e)}pán Obdr{hacek over (z)}álek
CPC分类号： G05D1/0253 , G05D1/0251 , G05D2201/0213 , G06T7/285
摘要： Methods and systems for egomotion estimation (e.g. of a vehicle) from visual inputs of a stereo pair of video cameras are described. 3D egomotion estimation is a six degrees of freedom problem in general. In embodiments of the present invention, this is simplified to four dimensions and further decomposed to two two-dimensional sub-solutions. The decomposition allows use of a voting strategy that identifies the most probable solution. An input is a set of image correspondences between two temporally consecutive stereo pairs, i.e. feature points do not need to be tracked over time. The experiments show that even if a trajectory is put together as a simple concatenation of frame-to-frame increments, the results are reliable and precise.
摘要翻译： 描述了从立体声视频摄像机的视觉输入中进行自动运动估计（例如车辆）的方法和系统。 一般来说，3D自由度估计是一个六自由度问题。 在本发明的实施例中，将其简化为四维并进一步分解为两个二维子解。 分解允许使用表示最可能解决方案的投票策略。 输入是两个时间上连续的立体声对之间的一组图像对应，即不需要随时间跟踪特征点。 实验表明，即使轨迹作为帧到帧增量的简单串联组合在一起，结果是可靠和准确的。
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公开(公告)号：US20090279792A1
公开(公告)日：2009-11-12
申请号：US12065437
申请日：2006-08-31
申请人： Stepan Obdrzalek , Jiri Matas , Katsuhiro Sakai
发明人： Stepan Obdrzalek , Jiri Matas , Katsuhiro Sakai
IPC分类号： G06K9/62
CPC分类号： G06F17/30247 , G06K9/6282
摘要： An image search method that is robust and fast (with computational complexity of logarithmic order relative to the number of models). The image search includes extracting a plurality of regions from one or more model images and normalizing the regions as standard regions; setting a specific region in each normalized standard region and classifying the plurality of standard regions under two or more subsets on the basis of a feature of the specific region; iteratively performing an operation of setting another specific region at a location different from that of the aforementioned specific region in each standard region classified in each subset and classifying the plurality of standard regions under still more subsets on the basis of a feature of the other specific region; and outputting the locations of the specific regions in the standard regions in the respective classifications and the features of the specific regions in the classifications.
摘要翻译： 一种稳健且快速的图像搜索方法（相对于模型数量的对数顺序的计算复杂度）。 图像搜索包括从一个或多个模型图像中提取多个区域并将该区域标准化为标准区域; 在每个标准化标准区域中设置特定区域，并且基于所述特定区域的特征将所述多个标准区域划分为两个或多个子集; 迭代地执行在分类在每个子集中的每个标准区域中的与上述特定区域不同的位置处设置另一特定区域的操作，并且基于另一个特定区域的特征对多个标准区域进行分类 ; 并且在分类中的各个分类和特定区域的特征中输出标准区域中的特定区域的位置。
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公开(公告)号：US08306332B2
公开(公告)日：2012-11-06
申请号：US12065437
申请日：2006-08-31
申请人： Stepan Obdrzalek , Jiri Matas , Katsuhiro Sakai
发明人： Stepan Obdrzalek , Jiri Matas , Katsuhiro Sakai
CPC分类号： G06F17/30247 , G06K9/6282
摘要： An image search method that is robust and fast (with computational complexity of logarithmic order relative to the number of models). The image search includes extracting a plurality of regions from one or more model images and normalizing the regions as standard regions; setting a specific region in each normalized standard region and classifying the plurality of standard regions under two or more subsets on the basis of a feature of the specific region; iteratively performing an operation of setting another specific region at a location different from that of the aforementioned specific region in each standard region classified in each subset and classifying the plurality of standard regions under still more subsets on the basis of a feature of the other specific region; and outputting the locations of the specific regions in the standard regions in the respective classifications and the features of the specific regions in the classifications.
摘要翻译： 一种稳健且快速的图像搜索方法（相对于模型数量的对数顺序的计算复杂度）。 图像搜索包括从一个或多个模型图像中提取多个区域并将该区域标准化为标准区域; 在每个标准化标准区域中设置特定区域，并且基于所述特定区域的特征将所述多个标准区域划分为两个或多个子集; 迭代地执行在分类在每个子集中的每个标准区域中的与上述特定区域不同的位置处设置另一特定区域的操作，并且基于另一个特定区域的特征对多个标准区域进行分类 ; 并且在分类中的各个分类和特定区域的特征中输出标准区域中的特定区域的位置。
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公开(公告)号：US20090290798A1
公开(公告)日：2009-11-26
申请号：US12065445
申请日：2006-08-31
申请人： Katsuhiro Sakai , Ondrej Chum , Jiri Matas
发明人： Katsuhiro Sakai , Ondrej Chum , Jiri Matas
IPC分类号： G06K9/46
CPC分类号： G06F17/30259 , G06K9/4671 , G06K9/6211
摘要： An image search method that is robust and fast (with computational complexity of logarithmic order relative to the number of models). The image search method including: extracting a plurality of specific regions possessing such a property that a shape can be normalized regardless of an affine transformation thereof, as affine-invariant regions from one or more learning images; calculating, with respect to a reference affine-invariant region, other neighboring affine-invariant regions as a set; deforming the neighboring affine-invariant regions by a transformation to normalize the shape of the reference affine-invariant region; and outputting the deformed shapes of the neighboring affine-invariant regions, together with combination of the reference affine-invariant region and the neighboring affine-invariant regions.
摘要翻译： 一种稳健且快速的图像搜索方法（相对于模型数量的对数顺序的计算复杂度）。 所述图像搜索方法包括：提取具有这样的特性的多个特定区域，即，无论其仿射变换，形状可以被归一化，作为来自一个或多个学习图像的仿射不变区域; 相对于参考仿射不变区域计算其他相邻仿射不变区域作为一组; 通过变换使邻近的仿射不变区域变形以使参考仿射不变区域的形状归一化; 并且输出相邻仿射不变区域的变形形状，以及参考仿射不变区域和相邻仿射不变区域的组合。
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公开(公告)号：US08295604B2
公开(公告)日：2012-10-23
申请号：US12065445
申请日：2006-08-31
申请人： Katsuhiro Sakai , Ondrej Chum , Jiri Matas
发明人： Katsuhiro Sakai , Ondrej Chum , Jiri Matas
CPC分类号： G06F17/30259 , G06K9/4671 , G06K9/6211
摘要： An image search method that is robust and fast (with computational complexity of logarithmic order relative to the number of models). The image search method including: extracting a plurality of specific regions possessing such a property that a shape can be normalized regardless of an affine transformation thereof, as affine-invariant regions from one or more learning images; calculating, with respect to a reference affine-invariant region, other neighboring affine-invariant regions as a set; deforming the neighboring affine-invariant regions by a transformation to normalize the shape of the reference affine-invariant region; and outputting the deformed shapes of the neighboring affine-invariant regions, together with combination of the reference affine-invariant region and the neighboring affine-invariant regions.
摘要翻译： 一种稳健且快速的图像搜索方法（相对于模型数量的对数顺序的计算复杂度）。 所述图像搜索方法包括：提取具有这样的特性的多个特定区域，即，无论其仿射变换，形状可以被归一化，作为来自一个或多个学习图像的仿射不变区域; 相对于参考仿射不变区域计算其他相邻仿射不变区域作为一组; 通过变换使邻近的仿射不变区域变形以使参考仿射不变区域的形状归一化; 并且输出相邻仿射不变区域的变形形状，以及参考仿射不变区域和相邻仿射不变区域的组合。
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