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公开(公告)号：US09380224B2
公开(公告)日：2016-06-28
申请号：US14193686
申请日：2014-02-28
Applicant: Microsoft Corporation
Inventor： Cem Keskin , Sean Ryan Francesco Fanello , Shahram Izadi , Pushmeet Kohli , David Kim , David Sweeney , Jamie Daniel Joseph Shotton , Duncan Paul Robertson , Sing Bing Kang
CPC classification number: H04N5/33 , G06K9/00201 , G06K9/2018 , G06K9/6219 , G06K9/6282 , G06T7/521 , G06T2200/04 , G06T2207/10028 , G06T2207/10048 , G06T2207/20081 , G06T2207/30201
Abstract: A method of sensing depth using an infrared camera. In an example method, an infrared image of a scene is received from an infrared camera. The infrared image is applied to a trained machine learning component which uses the intensity of image elements to assign all or some of the image elements a depth value which represents the distance between the surface depicted by the image element and the infrared camera. In various examples, the machine line component comprises one or more random decision forests.
Abstract translation: 使用红外摄像机感测深度的方法。 在一个示例方法中，从红外相机接收场景的红外图像。 将红外图像应用于训练有素的机器学习部件，其使用图像元素的强度来分配全部或部分图像元素，该深度值表示由图像元素描绘的表面与红外相机之间的距离。 在各种示例中，机器线路部件包括一个或多个随机决策树。
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公开(公告)号：US20150296152A1
公开(公告)日：2015-10-15
申请号：US14252638
申请日：2014-04-14
Applicant: Microsoft Corporation
Inventor： Sean Ryan Francesco Fanello , Cem Keskin , Pushmeet Kohli , Shahram Izadi , Jamie Daniel Joseph Shotton , Antonio Criminisi
CPC classification number: G06K9/52 , G06K9/0051 , G06K9/40 , G06K9/6268 , G06T5/002 , G06T5/20 , G06T2207/10028 , G06T2207/20081 , H04N5/217
Abstract: Filtering sensor data is described, for example, where filters conditioned on a local appearance of the signal are predicted by a machine learning system, and used to filter the sensor data. In various examples the sensor data is a stream of noisy video image data and the filtering process denoises the video stream. In various examples the sensor data is a depth image and the filtering process refines the depth image which may then be used for gesture recognition or other purposes. In various examples the sensor data is one dimensional measurement data from an electric motor and the filtering process denoises the measurements. In examples the machine learning system comprises a random decision forest where trees of the forest store filters at their leaves. In examples, the random decision forest is trained using a training objective with a data dependent regularization term.
Abstract translation: 对过滤传感器数据进行描述，例如，其中通过机器学习系统预测基于信号的局部外观的滤波器，并且用于过滤传感器数据。 在各种示例中，传感器数据是噪声视频图像数据流，并且滤波处理去除视频流。 在各种示例中，传感器数据是深度图像，并且滤波处理优化深度图像，然后可以将其用于手势识别或其他目的。 在各种示例中，传感器数据是来自电动机的一维测量数据，并且滤波处理去除了测量结果。 在实例中，机器学习系统包括森林商店的树木在其叶子处过滤的随机决策树。 在实例中，使用具有数据相关正则化项的训练目标对随机决策树进行训练。
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公开(公告)号：US20150248764A1
公开(公告)日：2015-09-03
申请号：US14193686
申请日：2014-02-28
Applicant: Microsoft Corporation
Inventor： Cem Keskin , Sean Ryan Francesco Fanello , Shahram Izadi , Pushmeet Kohli , David Kim , David Sweeney , Jamie Daniel Joesph Shotton , Duncan Paul Robertson , Sing Bing Kang
CPC classification number: H04N5/33 , G06K9/00201 , G06K9/2018 , G06K9/6219 , G06K9/6282 , G06T7/521 , G06T2200/04 , G06T2207/10028 , G06T2207/10048 , G06T2207/20081 , G06T2207/30201
Abstract: A method of sensing depth using an infrared camera. In an example method, an infrared image of a scene is received from an infrared camera. The infrared image is applied to a trained machine learning component which uses the intensity of image elements to assign all or some of the image elements a depth value which represents the distance between the surface depicted by the image element and the infrared camera. In various examples, the machine line component comprises one or more random decision forests.
Abstract translation: 使用红外摄像机感测深度的方法。 在一个示例方法中，从红外相机接收场景的红外图像。 将红外图像应用于训练有素的机器学习部件，其使用图像元素的强度来分配全部或部分图像元素，该深度值表示由图像元素描绘的表面与红外相机之间的距离。 在各种示例中，机器线路部件包括一个或多个随机决策树。
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