-
公开(公告)号：US09955140B2
公开(公告)日：2018-04-24
申请号：US14645326
申请日：2015-03-11
Applicant: Microsoft Technology Licensing, LLC
Inventor： Christoph Rhemann , Emad Barsoum , Yao Shen , Simon P. Stachniak , Shahram Izadi
CPC classification number: H04N13/214 , G06K9/00255 , G06K9/00288 , G06K9/00375 , G06K9/00892 , G06K9/2018 , G06K9/38 , G06T7/11 , G06T7/194 , G06T2207/10024 , G06T2207/10048 , H04N5/33 , H04N2213/003
Abstract: An initial candidate foreground region is identified within an infrared image that includes pixels exhibiting infrared intensity values within a pre-defined range. A depth of surfaces within the initial candidate foreground region is estimated based on infrared intensity values the pixels of the initial candidate foreground region. The initial candidate foreground region is expanded to an expanded candidate foreground region based on a body-model estimate. The body model estimate is seeded with one or more of the initial candidate foreground region, the depth of surfaces, and/or a face of a human subject identified by facial recognition. Each pixel of the infrared image is identified as either a foreground pixel or a background pixel based on a distance of that pixel relative to the expanded candidate foreground region. Pixels identified as background pixels may be modified within a corresponding visible light image.
-
公开(公告)号：US20170270390A1
公开(公告)日：2017-09-21
申请号：US15071111
申请日：2016-03-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sean Ryan Francesco Fanello , Shahram Izadi , Pushmeet Kohli , Christoph Rhemann , Shenlong Wang
IPC: G06K9/62
CPC classification number: G06K9/6282 , G06K9/00208 , G06K9/6219 , G06K9/6256
Abstract: Correspondences in content items may be determined using a trained decision tree to detect distinctive matches between portions of content items. The techniques described include determining a first group of patches associated with a first content item and processing a first patch based at least partly on causing the first patch to move through a decision tree, and determining a second group of patches associated with a second content item and processing a second patch based at least partly on causing the second patch to move through the decision tree. The techniques described include determining that the first patch and the second patch are associated with a same leaf node of the decision tree and determining that the first patch and the second patch are corresponding patches based at least partly on determining that the first patch and the second patch are associated with the same leaf node.
-
公开(公告)号：US10726255B2
公开(公告)日：2020-07-28
申请号：US13924464
申请日：2013-06-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Adam G. Kirk , Christoph Rhemann , Oliver A. Whyte , Shahram Izadi , Sing Bing Kang
IPC: G06K9/00 , H04N5/33 , G06K9/62 , G06F11/30 , G06F3/06 , G06F9/30 , G06F12/02 , G06F12/00 , B29C64/386 , H04N13/128 , H04N13/25 , H04N13/254 , H04N13/271 , G06T7/586 , H04N5/225 , H04N9/04 , H04N17/00 , G01B11/25 , G06T1/60 , B29C64/00 , H04N13/239 , G02B27/42 , G02B5/18 , G02B27/44 , G01B11/22 , G06T7/00 , H04N13/00 , A63F13/213
Abstract: Systems and methods for stereo matching based upon active illumination using a patch in a non-actively illuminated image to obtain weights that are used in patch similarity determinations in actively illuminated stereo images is provided. To correlate pixels in actively illuminated stereo images, adaptive support weights computations are used to determine similarity of patches corresponding to the pixels. In order to obtain adaptive support weights for the adaptive support weights computations, weights are obtained by processing a non-actively illuminated (“clean”) image.
-
公开(公告)号：US11265534B2
公开(公告)日：2022-03-01
申请号：US14176064
申请日：2014-02-08
Applicant: Microsoft Technology Licensing, LLC
Inventor： Adam G. Kirk , Christoph Rhemann , Oliver A. Whyte , Shahram Izadi , Sing Bing Kang , Andreas Georgiou
IPC: H04N13/363 , G01B11/16 , H04N5/33 , H04N9/31
Abstract: The subject disclosure is directed towards controlling the intensity of illumination of a scene or part of a scene, including to conserve illumination power. Quality of depth data in stereo images may be measured with different illumination states; environmental conditions, such as ambient light, natural texture may affect the quality. The illumination intensity may be controllably varied to obtain sufficient quality while conserving power. The control may be directed to one or more regions of interest corresponding to an entire scene or part of a scene.
-
公开(公告)号：US10929658B2
公开(公告)日：2021-02-23
申请号：US13924464
申请日：2013-06-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Adam G. Kirk , Christoph Rhemann , Oliver A. Whyte , Shahram Izadi , Sing Bing Kang
IPC: G06K9/00 , H04N5/33 , G06K9/62 , G06F11/30 , G06F3/06 , G06F9/30 , G06F12/02 , G06F12/00 , B29C64/386 , H04N13/128 , H04N13/25 , H04N13/254 , H04N13/271 , G06T7/586 , H04N5/225 , H04N9/04 , H04N17/00 , G01B11/25 , G06T1/60 , B29C64/00 , H04N13/239 , G02B27/42 , G02B5/18 , G02B27/44 , G01B11/22 , G06T7/00 , H04N13/00 , A63F13/213
Abstract: Systems and methods for stereo matching based upon active illumination using a patch in a non-actively illuminated image to obtain weights that are used in patch similarity determinations in actively illuminated stereo images is provided. To correlate pixels in actively illuminated stereo images, adaptive support weights computations are used to determine similarity of patches corresponding to the pixels. In order to obtain adaptive support weights for the adaptive support weights computations, weights are obtained by processing a non-actively illuminated (“clean”) image.
-
Patent Agency Ranking
公开(公告)号：US09886652B2
公开(公告)日：2018-02-06
申请号：US15071111
申请日：2016-03-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sean Ryan Francesco Fanello , Shahram Izadi , Pushmeet Kohli , Christoph Rhemann , Shenlong Wang
IPC: G06K9/62
CPC classification number: G06K9/6282 , G06K9/00208 , G06K9/6219 , G06K9/6256
Abstract: Correspondences in content items may be determined using a trained decision tree to detect distinctive matches between portions of content items. The techniques described include determining a first group of patches associated with a first content item and processing a first patch based at least partly on causing the first patch to move through a decision tree, and determining a second group of patches associated with a second content item and processing a second patch based at least partly on causing the second patch to move through the decision tree. The techniques described include determining that the first patch and the second patch are associated with a same leaf node of the decision tree and determining that the first patch and the second patch are corresponding patches based at least partly on determining that the first patch and the second patch are associated with the same leaf node.
-
公开(公告)号：US20170236286A1
公开(公告)日：2017-08-17
申请号：US15071133
申请日：2016-03-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sean Ryan Francesco Fanello , Christoph Rhemann , Adarsh Prakash Murthy Kowdle , Vladimir Tankovich , David KIM , Shahram Izadi
CPC classification number: G06K9/6282 , G06K9/627 , G06T7/0057 , G06T7/521 , G06T2207/10028 , G06T2207/20081
Abstract: Techniques for determining depth for a visual content item using machine-learning classifiers include obtaining a visual content item of a reference light pattern projected onto an object, and determining shifts in locations of pixels relative to other pixels representing the reference light pattern. Disparity, and thus depth, for pixels may be determined by executing one or more classifiers trained to identify disparity for pixels based on the shifts in locations of the pixels relative to other pixels of a visual content item depicting in the reference light pattern. Disparity for pixels may be determined using a visual content item of a reference light pattern projected onto an object without having to match pixels between two visual content items, such as a reference light pattern and a captured visual content item.
-
公开(公告)号：US20160269714A1
公开(公告)日：2016-09-15
申请号：US14645326
申请日：2015-03-11
Applicant: Microsoft Technology Licensing, LLC
Inventor： Christoph Rhemann , Emad Barsoum , Yao Shen , Simon P. Stachniak , Shahram Izadi
CPC classification number: H04N13/214 , G06K9/00255 , G06K9/00288 , G06K9/00375 , G06K9/00892 , G06K9/2018 , G06K9/38 , G06T7/11 , G06T7/194 , G06T2207/10024 , G06T2207/10048 , H04N5/33 , H04N2213/003
Abstract: An initial candidate foreground region is identified within an infrared image that includes pixels exhibiting infrared intensity values within a pre-defined range. A depth of surfaces within the initial candidate foreground region is estimated based on infrared intensity values the pixels of the initial candidate foreground region. The initial candidate foreground region is expanded to an expanded candidate foreground region based on a body-model estimate. The body model estimate is seeded with one or more of the initial candidate foreground region, the depth of surfaces, and/or a face of a human subject identified by facial recognition. Each pixel of the infrared image is identified as either a foreground pixel or a background pixel based on a distance of that pixel relative to the expanded candidate foreground region. Pixels identified as background pixels may be modified within a corresponding visible light image.
Abstract translation: 在包括在预定义范围内呈现红外强度值的像素的红外图像内识别初始候选前景区域。 基于初始候选前景区域的像素的红外强度值来估计初始候选前景区域内的表面深度。 基于身体模型估计将初始候选前景区域扩展到扩展的候选前景区域。 用人脸识别识别的人类对象的初始候选前景区域，表面深度和/或人脸的一个或多个种子接种身体模型估计。 基于该像素相对于扩展的候选前景区域的距离，将红外图像的每个像素识别为前景像素或背景像素。 识别为背景像素的像素可以在相应的可见光图像内被修改。
-
公开(公告)号：US09916524B2
公开(公告)日：2018-03-13
申请号：US15071133
申请日：2016-03-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sean Ryan Francesco Fanello , Christoph Rhemann , Adarsh Prakash Murthy Kowdle , Vladimir Tankovich , David Kim , Shahram Izadi
CPC classification number: G06K9/6282 , G06K9/627 , G06T7/0057 , G06T7/521 , G06T2207/10028 , G06T2207/20081
Abstract: Techniques for determining depth for a visual content item using machine-learning classifiers include obtaining a visual content item of a reference light pattern projected onto an object, and determining shifts in locations of pixels relative to other pixels representing the reference light pattern. Disparity, and thus depth, for pixels may be determined by executing one or more classifiers trained to identify disparity for pixels based on the shifts in locations of the pixels relative to other pixels of a visual content item depicting in the reference light pattern. Disparity for pixels may be determined using a visual content item of a reference light pattern projected onto an object without having to match pixels between two visual content items, such as a reference light pattern and a captured visual content item.
-
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.
-
-
-
-
-
-
-
-
-
Search Results
14
records
(took 0.039 seconds)
