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公开(公告)号：US20110085705A1
公开(公告)日：2011-04-14
申请号：US12972837
申请日：2010-12-20
Applicant: Shahram Izadi , Jamie Shotton , John Winn , Antonio Criminisi , Otmar Hilliges , Mat Cook , David Molyneaux
Inventor： Shahram Izadi , Jamie Shotton , John Winn , Antonio Criminisi , Otmar Hilliges , Mat Cook , David Molyneaux
IPC: G06K9/00
CPC classification number: G06K9/00369
Abstract: A system and method for detecting and tracking targets including body parts and props is described. In one aspect, the disclosed technology acquires one or more depth images, generates one or more classification maps associated with one or more body parts and one or more props, tracks the one or more body parts using a skeletal tracking system, tracks the one or more props using a prop tracking system, and reports metrics regarding the one or more body parts and the one or more props. In some embodiments, feedback may occur between the skeletal tracking system and the prop tracking system.
Abstract translation: 描述了用于检测和跟踪包括身体部位和道具的目标的系统和方法。 一方面，所公开的技术获取一个或多个深度图像，生成与一个或多个身体部位和一个或多个道具相关联的一个或多个分类图，使用骨骼跟踪系统跟踪该一个或多个身体部位， 使用道具跟踪系统的更多道具，并且报告关于一个或多个身体部位和一个或多个道具的指标。 在一些实施例中，可以在骨骼跟踪系统和支架跟踪系统之间进行反馈。
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公开(公告)号：US08213680B2
公开(公告)日：2012-07-03
申请号：US12727787
申请日：2010-03-19
Applicant: Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
Inventor： Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
CPC classification number: G06K9/6256 , G06K9/00335 , G06K9/6206
Abstract: Synthesized body images are generated for a machine learning algorithm of a body joint tracking system. Frames from motion capture sequences are retargeted to several different body types, to leverage the motion capture sequences. To avoid providing redundant or similar frames to the machine learning algorithm, and to provide a compact yet highly variegated set of images, dissimilar frames can be identified using a similarity metric. The similarity metric is used to locate frames which are sufficiently distinct, according to a threshold distance. For realism, noise is added to the depth images based on noise sources which a real world depth camera would often experience. Other random variations can be introduced as well. For example, a degree of randomness can be added to retargeting. For each frame, the depth image and a corresponding classification image, with labeled body parts, are provided. 3-D scene elements can also be provided.
Abstract translation: 为身体关节跟踪系统的机器学习算法生成合成身体图像。 来自运动捕捉序列的帧被重定向到几种不同的身体类型，以利用运动捕捉序列。 为了避免向机器学习算法提供冗余或相似的帧，并且为了提供紧凑但高度变化的图像集合，可以使用相似性度量来识别不同的帧。 相似性度量用于根据阈值距离定位足够明显的帧。 对于现实主义，基于真实世界深度相机经常会遇到的噪声源，将噪声添加到深度图像。 也可以引入其他随机变化。 例如，可以添加一定程度的随机性来重定向。 对于每个帧，提供深度图像和具有标记的身体部分的相应分类图像。 也可以提供3-D场景元素。
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公开(公告)号：US08660303B2
公开(公告)日：2014-02-25
申请号：US12972837
申请日：2010-12-20
Applicant: Shahram Izadi , Jamie Shotton , John Winn , Antonio Criminisi , Otmar Hilliges , Mat Cook , David Molyneaux
Inventor： Shahram Izadi , Jamie Shotton , John Winn , Antonio Criminisi , Otmar Hilliges , Mat Cook , David Molyneaux
CPC classification number: G06K9/00369
Abstract: A system and method for detecting and tracking targets including body parts and props is described. In one aspect, the disclosed technology acquires one or more depth images, generates one or more classification maps associated with one or more body parts and one or more props, tracks the one or more body parts using a skeletal tracking system, tracks the one or more props using a prop tracking system, and reports metrics regarding the one or more body parts and the one or more props. In some embodiments, feedback may occur between the skeletal tracking system and the prop tracking system.
Abstract translation: 描述了用于检测和跟踪包括身体部位和道具的目标的系统和方法。 在一个方面，所公开的技术获取一个或多个深度图像，生成与一个或多个身体部位和一个或多个道具相关联的一个或多个分类图，使用骨骼跟踪系统跟踪一个或多个身体部位， 使用道具跟踪系统的更多道具，并且报告关于一个或多个身体部位和一个或多个道具的指标。 在一些实施例中，可以在骨骼跟踪系统和支架跟踪系统之间进行反馈。
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公开(公告)号：US20110228976A1
公开(公告)日：2011-09-22
申请号：US12727787
申请日：2010-03-19
Applicant: Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
Inventor： Andrew Fitzgibbon , Jamie Shotton , Mat Cook , Richard Moore , Mark Finnochio
CPC classification number: G06K9/6256 , G06K9/00335 , G06K9/6206
Abstract: Synthesized body images are generated for a machine learning algorithm of a body joint tracking system. Frames from motion capture sequences are retargeted to several different body types, to leverage the motion capture sequences. To avoid providing redundant or similar frames to the machine learning algorithm, and to provide a compact yet highly variegated set of images, dissimilar frames can be identified using a similarity metric. The similarity metric is used to locate frames which are sufficiently distinct, according to a threshold distance. For realism, noise is added to the depth images based on noise sources which a real world depth camera would often experience. Other random variations can be introduced as well. For example, a degree of randomness can be added to retargeting. For each frame, the depth image and a corresponding classification image, with labeled body parts, are provided. 3-D scene elements can also be provided.
Abstract translation: 为身体关节跟踪系统的机器学习算法生成合成身体图像。 来自运动捕捉序列的帧被重定向到几种不同的身体类型，以利用运动捕捉序列。 为了避免向机器学习算法提供冗余或相似的帧，并且为了提供紧凑但高度变化的图像集合，可以使用相似性度量来识别不同的帧。 相似性度量用于根据阈值距离定位足够明显的帧。 对于现实主义，基于真实世界深度相机经常会遇到的噪声源，将噪声添加到深度图像。 也可以引入其他随机变化。 例如，可以添加一定程度的随机性来重定向。 对于每个帧，提供深度图像和具有标记的身体部分的相应分类图像。 也可以提供3-D场景元素。
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