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公开(公告)号：US10712204B2
公开(公告)日：2020-07-14
申请号：US15430256
申请日：2017-02-10
Applicant: Google Inc.
Inventor： Yash Modi , Mark Rajan Malhotra , Gwendolyn van der Linden , Dongeek Shin , Michael Dixon
IPC: G01J5/00 , G08B13/193 , G08B13/191 , G01J5/02 , G01J5/10
Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.
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公开(公告)号：US10942196B2
公开(公告)日：2021-03-09
申请号：US15676564
申请日：2017-08-14
Applicant: Google Inc.
Inventor： Mark Rajan Malhotra , Gwendolyn van der Linden , Yash Modi , Dongeek Shin
Abstract: Systems and methods of detecting human movement with a sensor are provided, including generating a motion event signal in response to movement detected by the sensor, and generating a parameterized curve to represent the detected motion. The parameterized curve is fit to a predetermined window of sensor data captured by the sensor to filter the motion event signal. A noise magnitude estimate and a curve fit error is determined based on the fitted parameterized curve to the predetermined window. A detection threshold value is determined based on the curve fit error, a noise source signal estimate of known noise, and zero or more noise magnitudes from other sources. Human motion is determined by correlating a true motion event signal with human motion based on a comparison between a value of a point on the parameterized curve and the detection threshold value.
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公开(公告)号：US20190049479A1
公开(公告)日：2019-02-14
申请号：US15676564
申请日：2017-08-14
Applicant: Google Inc.
Inventor： Mark Rajan Malhotra , Gwendolyn van der Linden , Yash Modi , Dongeek Shin
Abstract: Systems and methods of detecting human movement with a sensor are provided, including generating a motion event signal in response to movement detected by the sensor, and generating a parameterized curve to represent the detected motion. The parameterized curve is fit to a predetermined window of sensor data captured by the sensor to filter the motion event signal. A noise magnitude estimate and a curve fit error is determined based on the fitted parameterized curve to the predetermined window. A detection threshold value is determined based on the curve fit error, a noise source signal estimate of known noise, and zero or more noise magnitudes from other sources. Human motion is determined by correlating a true motion event signal with human motion based on a comparison between a value of a point on the parameterized curve and the detection threshold value.
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公开(公告)号：US20180231419A1
公开(公告)日：2018-08-16
申请号：US15430256
申请日：2017-02-10
Applicant: Google Inc.
Inventor： Yash Modi , Mark Rajan Malhotra , Gwendolyn van der Linden , Dongeek Shin , Michael Dixon
CPC classification number: G01J5/0025 , G01J5/025 , G01J5/10 , G08B13/191 , G08B13/193
Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.
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