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公开(公告)号：US20140267802A1
公开(公告)日：2014-09-18
申请号：US13909700
申请日：2013-06-04
Applicant: Apple Inc.
Inventor： Todd Sachs , Marius Tico , Rolf Toft , Paul Hubel , George Williams
CPC classification number: H04N5/23267 , H04N5/23254 , H04N5/23258 , H04N5/2356
Abstract: Techniques are disclosed for selectively capturing, retaining, and combining multiple sub-exposure images or brackets to yield a final image having diminished motion-induced blur and good noise characteristics. More specifically, after or during the capture of N brackets, the M best may be identified for combining into a single output image, (N>M). As used here, the term “best” means those brackets that exhibit the least amount of relative motion with respect to one another—with one caveat: integer pixel shifts may be preferred over sub-pixel shifts.
Abstract translation: 公开了用于选择性地捕获，保留和组合多个次曝光图像或括号以产生具有减小的运动引起的模糊和良好噪声特性的最终图像的技术。 更具体地说，在捕获N个括号之后或期间，可以识别M最佳以组合成单个输出图像（N> M）。 如这里所使用的，术语“最佳”是指相对于彼此表现出最小量的相对运动的括号 - 一个值得注意的是：整数像素偏移可能优于子像素位移。
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公开(公告)号：US09542585B2
公开(公告)日：2017-01-10
申请号：US13911983
申请日：2013-06-06
Applicant: Apple Inc.
Inventor： George Williams , Benjamin Olson , Sebastien Beysserie , Ethan Tira-Thompson , Jianping Zhou , Claus Molgaard , Todd Sachs , Rudolph van der Merwe , Marco Zuliani
CPC classification number: G06K7/1443 , G06K7/10722 , G06K9/3233 , G06K9/6203 , G06K2009/3291 , G06K2209/21 , G06T7/20
Abstract: A method to improve the efficiency of the detection and tracking of machine-readable objects is disclosed. The properties of image frames may be pre-evaluated to determine whether a machine-readable object, even if present in the image frames, would be likely to be detected. After it is determined that one or more image frames have properties that may enable the detection of a machine-readable object, image data may be evaluated to detect the machine-readable object. When a machine-readable object is detected, the location of the machine-readable object in a subsequent frame may be determined based on a translation metric between the image frame in which the object was identified and the subsequent frame rather than a detection of the object in the subsequent frame. The translation metric may be identified based on an evaluation of image data and/or motion sensor data associated with the image frames.
Abstract translation: 公开了一种提高机器可读对象检测和跟踪效率的方法。 可以预先评估图像帧的属性，以确定即使存在于图像帧中的机器可读对象是否可能被检测到。 在确定一个或多个图像帧具有能够检测机器可读对象的属性之后，可以评估图像数据以检测机器可读对象。 当检测到机器可读对象时，可以基于在其中识别对象的图像帧与后续帧之间的转换度量而不是对象的检测来确定随后帧中的机器可读对象的位置 在后续的框架。 可以基于与图像帧相关联的图像数据和/或运动传感器数据的评估来识别翻译度量。
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公开(公告)号：US20140363044A1
公开(公告)日：2014-12-11
申请号：US13911983
申请日：2013-06-06
Applicant: Apple Inc.
Inventor： George Williams , Benjamin Olson , Sebastien Beysserie , Ethan Tira-Thompson , Jianping Zhou , Claus Molgaard , Todd Sachs , Rudolph van der Merwe , Marco Zuliani
IPC: G06K9/00
CPC classification number: G06K7/1443 , G06K7/10722 , G06K9/3233 , G06K9/6203 , G06K2009/3291 , G06K2209/21 , G06T7/20
Abstract: A method to improve the efficiency of the detection and tracking of machine-readable objects is disclosed. The properties of image frames may be pre-evaluated to determine whether a machine-readable object, even if present in the image frames, would be likely to be detected. After it is determined that one or more image frames have properties that may enable the detection of a machine-readable object, image data may be evaluated to detect the machine-readable object. When a machine-readable object is detected, the location of the machine-readable object in a subsequent frame may be determined based on a translation metric between the image frame in which the object was identified and the subsequent frame rather than a detection of the object in the subsequent frame. The translation metric may be identified based on an evaluation of image data and/or motion sensor data associated with the image frames.
Abstract translation: 公开了一种提高机器可读对象检测和跟踪效率的方法。 可以预先评估图像帧的属性，以确定即使存在于图像帧中的机器可读对象是否可能被检测到。 在确定一个或多个图像帧具有能够检测机器可读对象的属性之后，可以评估图像数据以检测机器可读对象。 当检测到机器可读对象时，可以基于在其中识别对象的图像帧与后续帧之间的转换度量而不是对象的检测来确定随后帧中的机器可读对象的位置 在后续的框架。 可以基于与图像帧相关联的图像数据和/或运动传感器数据的评估来识别翻译度量。
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公开(公告)号：US09357130B2
公开(公告)日：2016-05-31
申请号：US13909700
申请日：2013-06-04
Applicant: Apple Inc.
Inventor： Todd Sachs , Marius Tico , Rolf Toft , Paul Hubel , George Williams
CPC classification number: H04N5/23267 , H04N5/23254 , H04N5/23258 , H04N5/2356
Abstract: Techniques are disclosed for selectively capturing, retaining, and combining multiple sub-exposure images or brackets to yield a final image having diminished motion-induced blur and good noise characteristics. More specifically, after or during the capture of N brackets, the M best may be identified for combining into a single output image, (N>M). As used here, the term “best” means those brackets that exhibit the least amount of relative motion with respect to one another—with one caveat: integer pixel shifts may be preferred over sub-pixel shifts.
Abstract translation: 公开了用于选择性地捕获，保留和组合多个次曝光图像或括号以产生具有减小的运动引起的模糊和良好噪声特性的最终图像的技术。 更具体地说，在捕获N个括号之后或期间，可以识别M最佳以组合成单个输出图像（N> M）。 如这里所使用的，术语“最佳”是指相对于彼此表现出最小量的相对运动的括号 - 一个值得注意的是：整数像素偏移可能优于子像素位移。
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