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公开(公告)号：US10311282B2
公开(公告)日：2019-06-04
申请号：US15701170
申请日：2017-09-11
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jamie Daniel Joseph Shotton , Cem Keskin , Christoph Rhemann , Toby Sharp , Duncan Paul Robertson , Pushmeet Kohli , Andrew William Fitzgibbon , Shahram Izadi
IPC: G06T7/11 , G01S17/36 , G06K9/00 , G01S17/89 , G06K9/62 , G01S17/10 , G01S7/48 , G01S7/491 , G06T7/50
Abstract: Region of interest detection in raw time of flight images is described. For example, a computing device receives at least one raw image captured for a single frame by a time of flight camera. The raw image depicts one or more objects in an environment of the time of flight camera (such as human hands, bodies or any other objects). The raw image is input to a trained region detector and in response one or more regions of interest in the raw image are received. A received region of interest comprises image elements of the raw image which are predicted to depict at least part of one of the objects. A depth computation logic computes depth from the one or more regions of interest of the raw image.
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Patent Agency Ranking
公开(公告)号：US20160104031A1
公开(公告)日：2016-04-14
申请号：US14513746
申请日：2014-10-14
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jamie Daniel Joseph Shotton , Cem Keskin , Christoph Rhemann , Toby Sharp , Duncan Paul Robertson , Pushmeet Kohli , Andrew William Fitzgibbon , Shahram Izadi
CPC classification number: G06K9/00201 , G01S7/4808 , G01S7/4911 , G01S17/10 , G01S17/36 , G01S17/89 , G06K9/00362 , G06K9/00671 , G06K9/6282 , G06T7/11 , G06T7/50 , G06T2207/10028 , G06T2207/10048 , G06T2207/10152 , G06T2207/20081
Abstract: Region of interest detection in raw time of flight images is described. For example, a computing device receives at least one raw image captured for a single frame by a time of flight camera. The raw image depicts one or more objects in an environment of the time of flight camera (such as human hands, bodies or any other objects). The raw image is input to a trained region detector and in response one or more regions of interest in the raw image are received. A received region of interest comprises image elements of the raw image which are predicted to depict at least part of one of the objects. A depth computation logic computes depth from the one or more regions of interest of the raw image.
Abstract translation: 描述飞行时间图像中的感兴趣区域检测。 例如，计算设备在飞行时间相机接收针对单个帧捕获的至少一个原始图像。 原始图像描绘了飞行时间相机（例如人的手，身体或任何其他物体）的环境中的一个或多个物体。 将原始图像输入到经过训练的区域检测器，并且作为响应，接收原始图像中的一个或多个感兴趣区域。 接收的感兴趣区域包括被预测为描绘其中一个对象的至少一部分的原始图像的图像元素。 深度计算逻辑从原始图像的一个或多个感兴趣区域计算深度。
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公开(公告)号：US09911032B2
公开(公告)日：2018-03-06
申请号：US15398680
申请日：2017-01-04
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jamie Daniel Joseph Shotton , Cem Keskin , Jonathan Taylor , Toby Sharp , Shahram Izadi , Andrew William Fitzgibbon , Pushmeet Kohli , Duncan Paul Robertson
CPC classification number: G06K9/00335 , G06F3/011 , G06F3/017 , G06F3/0304 , G06K9/00342 , G06K9/00355 , G06K9/52 , G06K9/6219 , G06K9/6263 , G06K9/6267 , G06K9/6282 , G06K9/66
Abstract: Tracking hand or body pose from image data is described, for example, to control a game system, natural user interface or for augmented reality. In various examples a prediction engine takes a single frame of image data and predicts a distribution over a pose of a hand or body depicted in the image data. In examples, a stochastic optimizer has a pool of candidate poses of the hand or body which it iteratively refines, and samples from the predicted distribution are used to replace some candidate poses in the pool. In some examples a best candidate pose from the pool is selected as the current tracked pose and the selection processes uses a 3D model of the hand or body.
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公开(公告)号：US09773155B2
公开(公告)日：2017-09-26
申请号：US14513746
申请日：2014-10-14
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jamie Daniel Joseph Shotton , Cem Keskin , Christoph Rhemann , Toby Sharp , Duncan Paul Robertson , Pushmeet Kohli , Andrew William Fitzgibbon , Shahram Izadi
IPC: G06T7/11 , G06K9/00 , G01S17/36 , G06K9/62 , G01S17/10 , G01S17/89 , G01S7/48 , G01S7/491 , G06T7/50
CPC classification number: G06K9/00201 , G01S7/4808 , G01S7/4911 , G01S17/10 , G01S17/36 , G01S17/89 , G06K9/00362 , G06K9/00671 , G06K9/6282 , G06T7/11 , G06T7/50 , G06T2207/10028 , G06T2207/10048 , G06T2207/10152 , G06T2207/20081
Abstract: Region of interest detection in raw time of flight images is described. For example, a computing device receives at least one raw image captured for a single frame by a time of flight camera. The raw image depicts one or more objects in an environment of the time of flight camera (such as human hands, bodies or any other objects). The raw image is input to a trained region detector and in response one or more regions of interest in the raw image are received. A received region of interest comprises image elements of the raw image which are predicted to depict at least part of one of the objects. A depth computation logic computes depth from the one or more regions of interest of the raw image.
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公开(公告)号：US20170116471A1
公开(公告)日：2017-04-27
申请号：US15398680
申请日：2017-01-04
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jamie Daniel Joseph Shotton , Cem Keskin , Jonathan Taylor , Toby Sharp , Shahram Izadi , Andrew William Fitzgibbon , Pushmeet Kohli , Duncan Paul Robertson
CPC classification number: G06K9/00335 , G06F3/011 , G06F3/017 , G06F3/0304 , G06K9/00342 , G06K9/00355 , G06K9/52 , G06K9/6219 , G06K9/6263 , G06K9/6267 , G06K9/6282 , G06K9/66
Abstract: Tracking hand or body pose from image data is described, for example, to control a game system, natural user interface or for augmented reality. In various examples a prediction engine takes a single frame of image data and predicts a distribution over a pose of a hand or body depicted in the image data. In examples, a stochastic optimizer has a pool of candidate poses of the hand or body which it iteratively refines, and samples from the predicted distribution are used to replace some candidate poses in the pool. In some examples a best candidate pose from the pool is selected as the current tracked pose and the selection processes uses a 3D model of the hand or body.
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公开(公告)号：US09552070B2
公开(公告)日：2017-01-24
申请号：US14494431
申请日：2014-09-23
Applicant: Microsoft Technology Licensing, LLC
Inventor： Jamie Daniel Joseph Shotton , Cem Keskin , Jonathan James Taylor , Toby Sharp , Shahram Izadi , Andrew William Fitzgibbon , Pushmeet Kohli , Duncan Paul Robertson
CPC classification number: G06K9/00335 , G06F3/011 , G06F3/017 , G06F3/0304 , G06K9/00342 , G06K9/00355 , G06K9/52 , G06K9/6219 , G06K9/6263 , G06K9/6267 , G06K9/6282 , G06K9/66
Abstract: Tracking hand or body pose from image data is described, for example, to control a game system, natural user interface or for augmented reality. In various examples a prediction engine takes a single frame of image data and predicts a distribution over a pose of a hand or body depicted in the image data. In examples, a stochastic optimizer has a pool of candidate poses of the hand or body which it iteratively refines, and samples from the predicted distribution are used to replace some candidate poses in the pool. In some examples a best candidate pose from the pool is selected as the current tracked pose and the selection processes uses a 3D model of the hand or body.
Abstract translation: 描述从图像数据跟踪手或身体姿势，例如，控制游戏系统，自然用户界面或增强现实。 在各种示例中，预测引擎采用单帧图像数据并且预测在图像数据中描绘的手或身体的姿势上的分布。 在示例中，随机优化器具有反复精炼的手或身体的候选姿势池，并且来自预测分布的样本用于替换池中的一些候选姿势。 在一些示例中，来自池的最佳候选姿势被选择为当前跟踪姿势，并且选择过程使用手或身体的3D模型。
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