Remote heart rate estimation
First Claim
1. A method comprising:
- detecting, by use of a processor, an object of interest (OOI) in each image of a video data;
tracking the OOI in each image of the video data;
identifying a region of interest (ROI) within the OOI;
generating a plurality of super pixels from a plurality of pixels in each ROI;
generating a super-pixel time series from the plurality of super pixels in each image;
removing interfering signals from the super-pixel time series;
modeling the super-pixel time series as a super-pixel model;
calculating a heart beat signal from the super-pixel model, wherein an ith super pixel for a time t is modeled as yi(t)=ui(t)+hi(t)+ni(t), where yi(t) is a measured pixel value, ui(t) is a background signal representing contributions to the measured pixel value due to movement and lighting variations, hi(t) is the heart beat signal, and ni(t) is a sensor noise signal representing contributions to the measured pixel value due to sensor noise; and
calculating heart characteristics from the heart beat signal, the heart characteristics comprising one or more of a heart rate, an inter-beat interval, and a heart rate variability.
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Accused Products
Abstract
For remote heart rate estimation, a method detects an object of interest (OOI) in each image of a video data and tracks the OOI in each image of the video data. The method identifies a region of interest (ROI) within the OOI and generates a plurality of super pixels from a plurality of pixels in each ROI. The method further generates a super-pixel time series from the plurality of super pixels in each image and removes interfering signals from the super-pixel time series. The method further models the super-pixel time series as a super-pixel model and calculates a heart beat signal from the super-pixel model. The method calculates heart characteristics from the heart beat signal. The heart characteristics include one or more of a heart rate, an inter-beat interval, and a heart rate variability.
10 Citations
20 Claims
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1. A method comprising:
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detecting, by use of a processor, an object of interest (OOI) in each image of a video data; tracking the OOI in each image of the video data; identifying a region of interest (ROI) within the OOI; generating a plurality of super pixels from a plurality of pixels in each ROI; generating a super-pixel time series from the plurality of super pixels in each image; removing interfering signals from the super-pixel time series; modeling the super-pixel time series as a super-pixel model; calculating a heart beat signal from the super-pixel model, wherein an ith super pixel for a time t is modeled as yi(t)=ui(t)+hi(t)+ni(t), where yi(t) is a measured pixel value, ui(t) is a background signal representing contributions to the measured pixel value due to movement and lighting variations, hi(t) is the heart beat signal, and ni(t) is a sensor noise signal representing contributions to the measured pixel value due to sensor noise; and calculating heart characteristics from the heart beat signal, the heart characteristics comprising one or more of a heart rate, an inter-beat interval, and a heart rate variability. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. An apparatus comprising:
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a camera; a processor; a memory storing code executable by the processor to perform; detecting an object of interest (OOI) in each image of a video data captured by the camera; tracking the OOI in each image of the video data; identifying a region of interest (ROI) within the OOI; generating a plurality of super pixels from a plurality of pixels in each ROI; generating a super-pixel time series from the plurality of super pixels in each image; removing interfering signals from the super-pixel time series; modeling the super-pixel time series as a super-pixel model; calculating a heart beat signal from the super-pixel model, wherein an ith super pixel for a time t is modeled as yi(t)=ui(t)+hi(t)+ni(t), where yi(t) is a measured pixel value, ui(t) is a background signal representing contributions to the measured pixel value due to movement and lighting variations, hi(t) is the heart beat signal, and ni(t) is a sensor noise signal representing contributions to the measured pixel value due to sensor noise; and calculating heart characteristics from the heart beat signal, the heart characteristics comprising one or more of a heart rate, an inter-beat interval, and a heart rate variability. - View Dependent Claims (17, 18)
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19. A program product comprising a non-transitory computer readable storage medium storing code executable by a processor to perform:
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detecting an object of interest (OOI) in each image of a video data captured by the camera; tracking the OOI in each image of the video data; identifying a region of interest (ROI) within the OOI; generating a plurality of super pixels from a plurality of pixels in each ROI; generating a super-pixel time series from the plurality of super pixels in each image; removing interfering signals from the super-pixel time series; modeling the super-pixel time series as a super-pixel model; calculating a heart beat signal from the super-pixel model, wherein an ith super pixel for a time t is modeled as yi(t)=ui(t)+hi(t)+ni(t), where yi(t) is a measured pixel value, ui(t) is a background signal representing contributions to the measured pixel value due to movement and lighting variations, hi(t) is the heart beat signal, and ni(t) is a sensor noise signal representing contributions to the measured pixel value due to sensor noise; and calculating heart characteristics from the heart beat signal, the heart characteristics comprising one or more of a heart rate, an inter-beat interval, and a heart rate variability. - View Dependent Claims (20)
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Specification