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    • 2. 发明申请
    • METHOD FOR POSE INVARIANT VESSEL FINGERPRINTING
    • 用于不定式船舶指纹的方法
    • US20100328452A1
    • 2010-12-30
    • US12758507
    • 2010-04-12
    • Sang-Hack JungAjay DivakaranHarpreet Singh Sawhney
    • Sang-Hack JungAjay DivakaranHarpreet Singh Sawhney
    • H04N7/18G06K9/46
    • G06K9/00771G06K9/6206G06K9/6211
    • A computer-implemented method for matching objects is disclosed. At least two images where one of the at least two images has a first target object and a second of the at least two images has a second target object are received. At least one first patch from the first target object and at least one second patch from the second target object are extracted. A distance-based part encoding between each of the at least one first patch and the at least one second patch based upon a corresponding codebook of image parts including at least one of part type and pose is constructed. A viewpoint of one of the at least one first patch is warped to a viewpoint of the at least one second patch. A parts level similarity measure based on the view-invariant distance measure for each of the at least one first patch and the at least one second patch is applied to determine whether the first target object and the second target object are the same or different objects.
    • 公开了一种用于匹配对象的计算机实现的方法。 接收至少两个图像,其中至少两个图像中的一个具有第一目标对象,并且至少两个图像中的第二图像具有第二目标对象。 提取来自第一目标对象的至少一个第一补丁和来自第二目标对象的至少一个第二补丁。 构建基于包括部件类型和姿态中的至少一个的图像部件的对应码本的至少一个第一贴片和至少一个第二贴片中的每一个之间的基于距离的部件编码。 所述至少一个第一贴片中的一个的视点弯曲到所述至少一个第二贴片的观点。 应用基于对于至少一个第一贴片和至少一个第二贴片中的每一个的视图不变距离度量的零件级相似性度量来确定第一目标对象和第二目标对象是相同还是不同的对象。
    • 3. 发明申请
    • CAMERA EGOMOTION ESTIMATION FROM AN INFRA-RED IMAGE SEQUENCE FOR NIGHT VISION
    • 来自夜视的红外图像序列的摄像机构估计
    • US20090207257A1
    • 2009-08-20
    • US12203322
    • 2008-09-03
    • Sang-Hack JungJayan Eledath
    • Sang-Hack JungJayan Eledath
    • H04N5/225
    • G06T7/246G06T7/73G06T2207/10016G06T2207/10048G06T2207/30244G06T2207/30252
    • A method for estimating egomotion of a camera mounted on a vehicle that uses infra-red images is disclosed, comprising the steps of (a) receiving a pair of frames from a plurality of frames from the camera, the first frame being assigned to a previous frame and an anchor frame and the second frame being assigned to a current frame; (b) extracting features from the previous frame and the current frame; (c) finding correspondances between extracted features from the previous frame and the current frame; and (d) estimating the relative pose of the camera by minimizing reprojection errors from the correspondences to the anchor frame. The method can further comprise the steps of (e) assigning the current frame as the anchor frame when a predetermined amount of image motion between the current frame and the anchor frame is observed; (f) assigning the current frame to the previous frame and assigning a new frame from the plurality of frames to the current frame; and (g) repeating steps (b)-(f) until there are no more frames from the plurality of frames to process. Step (c) is based on an estimation of the focus of expansion between the previous frame and the current frame.
    • 公开了一种用于估计安装在使用红外图像的车辆上的相机的自动运算的方法,包括以下步骤:(a)从相机从多个帧接收一对帧,将第一帧分配给先前的 帧和锚帧,并且第二帧被分配给当前帧; (b)从前一帧和当前帧中提取特征; (c)从前一帧和当前帧之间提取的特征之间的对应; 以及(d)通过使从与对应帧对应的重新投射误差最小化来估计相机的相对姿态。 该方法还可以包括以下步骤:(e)当观察到当前帧和锚帧之间的预定量的图像运动时,将当前帧分配为锚帧; (f)将当前帧分配给前一帧,并将新帧从多个帧分配给当前帧; 和(g)重复步骤(b) - (f),直到来自多个帧的帧不再有更多的处理。 步骤(c)基于对前一帧和当前帧之间的扩展重点的估计。
    • 10. 发明授权
    • Method for pose invariant vessel fingerprinting
    • 姿态不变血管指纹方法
    • US08330819B2
    • 2012-12-11
    • US12758507
    • 2010-04-12
    • Sang-Hack JungAjay DivakaranHarpreet Singh Sawhney
    • Sang-Hack JungAjay DivakaranHarpreet Singh Sawhney
    • H04N7/18
    • G06K9/00771G06K9/6206G06K9/6211
    • A computer-implemented method for for matching objects is disclosed. At least two images where one of the at least two images has a first target object and a second of the at least two images has a second target object are received. At least one first patch from the first target object and at least one second patch from the second target object are extracted. A distance-based part encoding between each of the at least one first patch and the at least one second patch based upon a corresponding codebook of image parts including at least one of part type and pose is constructed. A viewpoint of one of the at least one first patch is warped to a viewpoint of the at least one second patch. A parts level similarity measure based on the view-invariant distance measure for each of the at least one first patch and the at least one second patch is applied to determine whether the first target object and the second target object are the same or different objects.
    • 公开了一种用于匹配对象的计算机实现的方法。 接收至少两个图像,其中至少两个图像中的一个具有第一目标对象,并且至少两个图像中的第二图像具有第二目标对象。 提取来自第一目标对象的至少一个第一补丁和来自第二目标对象的至少一个第二补丁。 构建基于包括部件类型和姿态中的至少一个的图像部件的对应码本的至少一个第一贴片和至少一个第二贴片中的每一个之间的基于距离的部件编码。 所述至少一个第一贴片中的一个的视点弯曲到所述至少一个第二贴片的观点。 应用基于对于至少一个第一贴片和至少一个第二贴片中的每一个的视图不变距离度量的零件级相似性度量来确定第一目标对象和第二目标对象是相同还是不同的对象。