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1.发明授权Systems, circuits, and methods for efficient hierarchical object recognition based on clustered invariant features 有权基于聚类不变特征的有效分层对象识别的系统，电路和方法公开(公告)号：US09204112B2
公开(公告)日：2015-12-01
申请号：US13762267
申请日：2013-02-07
Applicant: STMicroelectronics S.r.l
Inventor： Paolo Pasteris , Giovanni Condello , Danilo Pietro Pau
CPC classification number: H04N19/124 , G06K9/00523 , G06K9/00671 , G06K9/46 , G06K9/4671 , G06K9/6218 , H04N19/13 , H04N19/91
Abstract: One embodiment is a method for selecting and grouping key points extracted by applying a feature detector on a scene being analyzed. The method includes grouping the extracted key points into clusters that enforce a geometric relation between members of a cluster, scoring and sorting the clusters, identifying and discarding clusters that are comprised of points which represent the background noise of the image, and sub-sampling the remaining clusters to provide a smaller number of key points for the scene.
Abstract translation: 一个实施例是一种用于选择和分组通过在正在分析的场景上应用特征检测器而提取的关键点的分组的方法。 该方法包括将所提取的关键点分组成强制簇的成员之间的几何关系，对聚类进行评分和排序，识别和丢弃由表示图像的背景噪声的点组成的簇，并对 剩余的群集为场景提供较少数量的关键点。
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公开(公告)号：US09569695B2
公开(公告)日：2017-02-14
申请号：US13869656
申请日：2013-04-24
Applicant: STMicroelectronics S.r.l.
Inventor： Danilo Pietro Pau , Paolo Pasteris , Mirko Falchetto
CPC classification number: G06K9/6228 , G06K9/32 , G06K9/46 , G06K2009/363 , G06T7/33 , G06T7/337 , H04N19/57
Abstract: Image-processing apparatus and methods to adaptively control a size and/or location of a visual search window used for feature matching in a machine-vision system are described. A search window controller may receive motion vector data and image recognition rate data, and compute a search window size and/or search window location based on the received data. The computed search window size may be a portion of an image frame. The motion vector data and image recognition rate data may be computed from one or more images in a video image sequence. By adaptively controlling search window size and location, an appreciable reduction in data processing burden for feature matching may be achieved.
Abstract translation: 描述了在机器视觉系统中自适应地控制用于特征匹配的视觉搜索窗口的尺寸和/或位置的图像处理设备和方法。 搜索窗口控制器可以接收运动矢量数据和图像识别率数据，并且基于接收到的数据来计算搜索窗口大小和/或搜索窗口位置。 所计算的搜索窗口大小可以是图像帧的一部分。 可以从视频图像序列中的一个或多个图像计算运动矢量数据和图像识别率数据。 通过自适应地控制搜索窗口大小和位置，可以实现特征匹配的数据处理负担的明显降低。
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3.发明申请SYSTEMS, CIRCUITS, AND METHODS FOR EFFICIENT HIERARCHICAL OBJECT RECOGNITION BASED ON CLUSTERED INVARIANT FEATURES 有权基于积分不变特征的高效分层对象识别的系统，电路和方法公开(公告)号：US20130216143A1
公开(公告)日：2013-08-22
申请号：US13762267
申请日：2013-02-07
Applicant: STMicroelectronics S.r.l
Inventor： Paolo Pasteris , Giovanni Condello , Danilo Pietro Pau
IPC: G06K9/62
CPC classification number: H04N19/124 , G06K9/00523 , G06K9/00671 , G06K9/46 , G06K9/4671 , G06K9/6218 , H04N19/13 , H04N19/91
Abstract: One embodiment is a method for selecting and grouping key points extracted by applying a feature detector on a scene being analyzed. The method includes grouping the extracted key points into clusters that enforce a geometric relation between members of a cluster, scoring and sorting the clusters, identifying and discarding clusters that are comprised of points which represent the background noise of the image, and sub-sampling the remaining clusters to provide a smaller number of key points for the scene.
Abstract translation: 一个实施例是一种用于选择和分组通过在正在分析的场景上应用特征检测器而提取的关键点的分组的方法。 该方法包括将所提取的关键点分组成强制簇的成员之间的几何关系，对聚类进行评分和排序，识别和丢弃由表示图像的背景噪声的点组成的簇，并对 剩余的群集为场景提供较少数量的关键点。
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