CN106778695A - A kind of many people's examing heartbeat fastly methods based on video - Google Patents

A kind of many people's examing heartbeat fastly methods based on video Download PDF

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CN106778695A
CN106778695A CN201710039731.0A CN201710039731A CN106778695A CN 106778695 A CN106778695 A CN 106778695A CN 201710039731 A CN201710039731 A CN 201710039731A CN 106778695 A CN106778695 A CN 106778695A
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face
heart rate
video
tracking
many people
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CN106778695B (en
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赵跃进
刘玲玲
刘明
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Beijing Institute of Technology BIT
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161—Detection; Localisation; Normalisation
    • G06V40/164—Detection; Localisation; Normalisation using holistic features
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/255—Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/30—Noise filtering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161—Detection; Localisation; Normalisation
    • G06V40/162—Detection; Localisation; Normalisation using pixel segmentation or colour matching

Abstract

The present invention relates to measuring of human health technical field, disclose a kind of many people's examing heartbeat fastly methods based on video, measured's video data is gathered by camera using cordless, and the color space of video data is converted into HSV by RGB, the heart rate for realizing many people is quickly measured.It is characterized in that, the method is by detecting the multiple human face regions in the video or existing video that are input into by camera with tracking and being partitioned into cheek region, extract the time-domain data sequence of cheek region and pre-processed, then switching to frequency domain carries out the extraction of heart rate.Compared with prior art, the present invention is accelerated based on improved Face datection algorithm with improved track algorithm and using multi-threading, can realize the examing heartbeat fastly of many people, shortens the time of heart rate measurement, improves the detection efficiency of physiological signal.

Description

A kind of many people's examing heartbeat fastly methods based on video
Technical field
Patent of the present invention is related to measuring of human health technical field, and in particular to one kind can realize that many people's rapid heart rates are surveyed The method of amount.
Background technology
Heart rate refers to the number of times of heart bounce per minute, different and different because of age, sex and other physiological conditions.Just The heart rate of raw youngster is quickly, reachable more than 130 beats/min.Heart rate when normal adult is quiet has significant individual difference, averagely exists 75 beats/min or so (between 60-100 beats/min).Same person, decreased heart rate, fluctuation of moving or be in a bad mood in quiet or sleep When increased heart rate.Therefore, heart rate can fully reflect the health of people, be the important physiology for carrying out self health monitoring Parameter, is also that doctor carries out the important evidence of medical diagnosis on disease to patient.
Heart rate can be divided into contact type measurement and non-contact measurement according to the difference of metering system.The generation of contact type measurement One of table is the goldstandard-electrocardiogram (EEG) of heart rate measurement, in addition with winding pectoral girdle, cuff or electrode wrist, finger tip, The contact measurement method of the positions such as ear-lobe, the disadvantage of contact measurement method be measurement complex operation, measure the cycle compared with Long and contact skin can bring discomfort to measured, and be based on the contactless survey of photoelectricity volume sphygmogram technology (IPPG) Amount method overcomes the shortcoming of contact method for measuring heart rate well, is to apply more extensive non-contact measurement side at present Method.
But, there is, measurement more sensitive for the change of light again in the contactless measurement based on existing IPPG Speed is low, measurement result is easily influenceed by motion artifact, heart rate measurements precision is low, most of hearts rate for being to be based on single people The problems such as measurement.
The content of the invention
1. it is contemplated that at least solving one of above-mentioned technical problem.
2. therefore, it is an object of the invention to propose a kind of contactless many people examing heartbeat fastly sides based on video Method, the method can be to the people in the video comprising multiple faces obtained by camera or the video containing multiple faces Face automatic detection and quick tracking, the human face region to obtaining can obtain the heart rate of each measured after analyzing and processing.
3. the method includes following part：Video acquisition part, Face datection part, face tracking part, ROI tones point It is aobvious that frame extracts part, time-domain signal fetching portion, signal procesing in time domain part, rate calculation part, face numbering and heart rate Show part；
4. video acquisition part described in, for selecting working method：One is to open camera, in the indoor ring of normal lighting Under border, determine that imaging device can be to fixing camera behind the position of human face region complete display imaging；Two is from one section of sheet The existing video comprising human face region in ground；
5. Face datection part described in, for detecting human face region from video, each human face region is numbered and is returned Face is numbered and heart rate display portion, and initializes face tracking part；
6. face tracking part described in, is tracked to each human face region that Face datection part detects；
7. part is extracted in ROI tones framing described in, for extract the color space in video per two field picture ROI region by RGB is converted to the value of Hue (tone) component after HSV；
8. time-domain signal fetching portion described in, for the face in every frame ROI region image to be marked off into cheek region, and To in tri- kinds of color components of this region HSV the capture of Hue (tone) components element gray average, cheek region H components when Domain signal value X (t)；
9. signal procesing in time domain part described in, for time-domain signal value X (t) for obtaining to be carried out into noise suppressed, signal Trending, the time-domain signal value after being processed
10. rate calculation part described in, for time-domain signal valueCarry out spectrum analysis and generate spectrogram, in frequency The crest frequency extracted in spectrogram in assigned frequency band carries out rate calculation；
Face numbering and heart rate display portion described in 11., for each face zone number marked to Face datection part And the heart rate value corresponding to the human face region that rate calculation part obtains is numbered shows in video.
Preferably, video acquisition part controls imaging device to realize by PC.
Preferably, Face datection part is realized by the classifier methods of loading nose simultaneously, face, positive face.
Preferably, what face tracking part was tracked by the improved compression for being adapted to many people of improved suitable multi-human tracking Method is realized.
Preferably, the framing of ROI tones extracts part by the way that color space is converted into HSV by RGB and the side of H components is extracted Method is realized.
Preferably, time-domain signal fetching portion is realized by extracting the method for the gray average of cheek region.
Preferably, signal procesing in time domain part passes through mean filter, small echo except hot-tempered, moving average method is realized.
Preferably, rate calculation part is realized by the method for Fast Fourier Transform (FFT).
Preferably, face numbering and heart rate display portion are realized by the method for multithreading.
Brief description of the drawings
1. Fig. 1 is method for measuring heart rate block diagram of the invention
2. Fig. 2 is the block diagram of each several part included by the present invention
3. Fig. 3 is method for measuring heart rate flow chart of the invention and multithreading schematic diagram
4. Fig. 4 is method for measuring heart rate Face datection partial process view of the invention
5. Fig. 5 is method for measuring heart rate face tracking partial process view of the invention
6. Fig. 6 is that the adjacent detection block position of method for measuring heart rate face tracking partial target detection block of the invention is closed System's figure
Specific embodiment
1. for the clear explanation objects, technical solutions and advantages of the present invention, below in conjunction with drawings and Examples, to this hair It is bright to be further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the present invention, it is not used to Limit the present invention.
2. as shown in figure 1, being many people's quick heart rate measuring method and step figures based on video of the invention.
3. as shown in Fig. 2 by frame of many people's quick heart rate measuring methods based on video of the invention comprising each several part Figure.
4. the first step, selects working method, the present invention to provide two kinds of working methods：One is directly to tested by camera Person carries out real-time heart rate detection, and two is that measured in local video carries out real-time heart rate detection.In two kinds of working methods Video be required for the selected suitable environment of illumination, determine that imaging device can and more complete imaging clear to human face region.With Lower step is with working method one as embodiment.
5. second step, starts imaging device, and the video acquisition of face is carried out to object to be measured, is then input into camera Video is decomposed into image sequence and RGB image is converted into gray-scale map, and permission face is in the range of image scene in gatherer process Mobile and deflection.
6. the 3rd step, judges that current face detects state, and Face datection part is started if face is not detected, until Face is detected, face numbering is returned into face numbering and heart rate display portion, and tracking section is initialized with testing result, Simultaneously by Face datection status indication to have detected that face, the workflow of the part is referring to Fig. 4.
7. the 4th step, starts face tracking part, and currently detected all faces are tracked respectively, and by tracking Module returning tracking state, continues next step if tracking successfully, otherwise returns to the 3rd step, and tracking process is referring to Fig. 5；In tracking Search radius be updated according to Fig. 6：Wherein, numbering is that 1~8 8 frames represent may be deposited around current goal frame respectively 8 frames of adjacent position, the cartographic represenation of area diverse location place track human faces area size of frame.By reference axis institute in figure Show, it is assumed that the parameter of target frame is respectively (x0,y0,w0,h0), four parameters represent the rectangle upper left corner corresponding to target frame successively Summit abscissa, ordinate, rectangle are wide, rectangle is high；Similarly, it can be assumed that 8 parameters of tracking box are (xi,yi,wi,hi), its Middle i takes 1,2,3,4,5,6,7,8 successively；Below so that distance between target frame and its upper right corner tracking box is calculated as an example, other feelings Condition is similar, now meets condition:
Obtaining minimum range is：
Then search radius are：
rsearch=lmin*0.8
8. the 5th step, each human face region (ROI) to tracking carries out mean filter, is partitioned into cheek region, extracts face The gray average of buccal region domain H components, and time-domain signal X (t) to obtaining carries out Wavelet Denoising Method, glide filter, signal and goes trend Change, obtain final time-domain signal
9. the 6th step, Fast Fourier Transform (FFT) is carried out to the time-domain signal that upper step is obtained, right between selection 0.5Hz~3Hz The frequency for answering spectrum value maximum, the frequency values correspond to numerical value per minute, as heart rate.Here 0.5Hz~3Hz the tables chosen Show that heart rate is in the situation of 30~180 bat/minutes, the scope that most hearts rate are likely to occur is contained, while eliminating it The interference of his physiological signal, the implementation process of the step is referring to the thread 2 in Fig. 3.
10. the 7th step, enables thread 3, and different faces are numbered into the display in real time of corresponding heart rate data in video.
11. beneficial effects：Compared with prior art, the present invention is based on image procossing, proposes a kind of quickly many people's hearts rate Measuring method, the acceleration of many people's heart rate detections is realized by multi-threading and improved track algorithm, by improved Detection algorithm and track algorithm reduce false drop rate, improve detection efficiency.

Claims (11)

1. a kind of many people's examing heartbeat fastly methods based on video, the method comprises the following steps：
S100, selection mode of operation, if then caller automatically opens up camera to direct mode of operation, if Working mould indirectly Then caller reads video to formula automatically, the human face region in then calling Face datection part to detect video；
S200, the human face region positional information that will be detected pass to face tracking part, start the tracking of face, while obtaining The image informations such as institute's track human faces area grayscale average；
S300, the image information of acquisition is processed and time-domain signal is converted into, then time-domain signal is filtered, is removed Make an uproar, go trending etc. to obtain preprocessed data after processing and start thread 2, frequency domain will be transformed to, frequency domain data is obtained, according to frequency Numeric field data calculates heart rate；
S400, startup thread 3, the numbering and its heart rate value of each detection object are shown in real time in video.
2. a kind of many people's examing heartbeat fastly methods based on video, the method is mainly used in daily noncontact heart rate measurement system In system, video is shot to the region comprising face using IP Camera, cell-phone camera first-class imaging device, realize automatic heart rate Measurement；Characterized in that, the method includes that ROI is extracted in video acquisition part, Face datection part, face tracking part, framing Partly, time-domain signal fetching portion, signal procesing in time domain part, rate calculation part, face numbering and heart rate display portion； The video acquisition part, for obtaining one section of color video frequency image comprising multiple human face regions or selection by camera Local video file；The Face datection part, the detection for carrying out face to the video image for gathering；The face tracking Part, for being tracked to the face for detecting, accelerates the processing speed per two field picture；The ROI tones framing extraction unit Point, the color space for extracting every frame picture is converted to the value of H (Hue) component after HSV by RGB；The time-domain signal is obtained Part is taken, for marking off cheek region from every frame ROI region, and the gray average of cheek region H components is asked for, as the frame The characteristic value of image, and generate time-domain signal X (t)；The signal procesing in time domain part, for time-domain signal X (t) that will be obtained Noise suppressed is carried out, the time-domain signal after being processedThe rate calculation part, for time-domain signal valueEnter Line frequency analysis of spectrum simultaneously generates spectrogram, and extracting the crest frequency in assigned frequency band in spectrogram carries out rate calculation.
3. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：In the step S200, specific bag Include following steps：
S201, set according to the distance between the tracking box and its closest tracking box size and position relationship in previous frame image Fixed new search radius；
Feature is extracted in S202, the sample gathered near the tracing positional according to new search radius and be mapped to lower dimensional space, Obtain region to be sorted；
S203, two Bayes classifiers obtained with previous frame are selected most respectively to these regions to be sorted to classifying The rectangle frame of target is likely to be, as current tracking result；
If judging currently to track the edge during object is moved into whole video pictures, mark tracking is unsuccessful, restarts Face detection module, and Current heart rate testing result is emptied, otherwise perform step S204；
S204, centered on present frame target area, take two groups of positive negative samples, be respectively：
1) with 4 pixels it is radius in target area, takes out 45 positive samples, with 8 is inside radius, 12 outside target area To randomly select 50 negative samples in the annulus of outer radius；
2) in target area with 4 pixels as it is interior be external diameter through 6 pixels, take out 60 positive samples, in target area Outer is inside radius with 12, and 16 in the annulus of outer radius to randomly select 60 negative samples；
S205, the integrogram and Haar feature extraction templates that calculate original image；
S206, the Haar feature extraction templates according to integrogram and gained, extract the feature of positive negative sample, update Bayes and separate Device, obtains new grader, and target in current frame image is tracked with the grader.
4. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：Taken the photograph using IP Camera or mobile phone Heart rate measurement is realized as the imaging device commonly used in first-class daily life.
5. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：There are two kinds of working methods optional, both Heart rate detection can also be carried out to the human face region in local video by the heart rate of camera direct detection measured.
6. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：The face detection module is by adding Manned face grader, nose grader, three graders of face grader reduce false drop rate, are carried out by treating detection image Histogram equalization reduction loss.
7. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：The face tracking module is to utilize Improved compression tracking (Compress Tracking) algorithm of the present invention, suppresses to be tracked during tracking by two methods The drift of frame, be respectively：
1) according to the 8 kinds of position relationships existed between the adjacent detection block of current detection frame, every kind of position is calculated respectively and is closed System under distance and therefrom select minimum range lmin, make search radius rsearch=lmin* 0.8, it is to avoid search radius are excessive to be caused The aliasing of feature extraction between each tracking target.
2) with 4 pixels it is respectively radius in target area using the thought of integrated study, takes out 45 positive samples, With 8 it is inside radius outside target area, 12 in the annulus of outer radius to randomly select 50 negative samples；It is internal diameter 6 with 4 pixels Individual pixel is external diameter, takes out 60 positive samples, with 12 is inside radius target area outside, 16 in the annulus of outer radius at random Choose 60 negative samples；Respectively by this two groups positive negative sample feeding graders, and grader under both of these case is returned respectively Maximum position average as tracking target position.
8. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：The face tracking module is detected Have in detection object after removing the detection visual field, empty the heart rate data of the object, exit face tracking part and restart face inspection Survey part.
9. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：Cheek is marked off from human face region Region, carries out the extraction of heart rate signal, it is to avoid blinking for eyes and blocking to ROI gray values for tested brow portion hair The influence for bringing, improves heart rate measurement precision.
10. a kind of many people's examing heartbeat fastly methods based on video, are accelerated, cardiotach ometer using multithreading to heart rate detection Calculate part and take single thread respectively with face numbering and heart rate display portion, the work of other modules is not influenceed, realize The quick detection of many people's hearts rate.
11. many people's examing heartbeat fastly methods according to claim 1, it is characterized in that：The face numbering and heart rate The order of the face that display portion is detected according to Face datection part marks its correspondence on each face tracking frame successively Numbering, and show the corresponding heart rate value of each measured successively according to numbering ascending order in video.
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Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107330945A (en) * 2017-07-05 2017-11-07 合肥工业大学 A kind of examing heartbeat fastly method based on video
CN107334469A (en) * 2017-07-24 2017-11-10 北京理工大学 Non-contact more people's method for measuring heart rate and device based on SVMs
CN107506716A (en) * 2017-08-17 2017-12-22 华东师范大学 A kind of contactless real-time method for measuring heart rate based on video image
CN109009052A (en) * 2018-07-02 2018-12-18 南京工程学院 The embedded heart rate measurement system and its measurement method of view-based access control model
CN109259748A (en) * 2018-08-17 2019-01-25 西安电子科技大学 The system and method for handset processes face video extraction heart rate signal
CN109480808A (en) * 2018-09-27 2019-03-19 深圳市君利信达科技有限公司 A kind of heart rate detection method based on PPG, system, equipment and storage medium
CN109871115A (en) * 2017-12-04 2019-06-11 腾讯科技（深圳）有限公司 Control method, device and computer readable storage medium in multimedia interactive
CN110276271A (en) * 2019-05-30 2019-09-24 福建工程学院 Merge the non-contact heart rate estimation technique of IPPG and depth information anti-noise jamming
GB2572961A (en) * 2018-04-16 2019-10-23 Clinicco Ltd System for vital sign detection from a video stream
CN110393513A (en) * 2018-04-25 2019-11-01 财团法人交大思源基金会 Contactless heartbeat measurement system, method and device thereof
CN110866498A (en) * 2019-11-15 2020-03-06 北京华宇信息技术有限公司 Portable heart rate monitoring device and heart rate monitoring method thereof
CN111281367A (en) * 2018-12-10 2020-06-16 绍兴图聚光电科技有限公司 Anti-interference non-contact heart rate detection method based on face video
CN111540169A (en) * 2020-04-24 2020-08-14 重庆城市管理职业学院 Bus danger alarm method and system based on intelligent behavior monitoring
CN112797840A (en) * 2021-01-28 2021-05-14 杭州屹道科技有限公司 Firearm handing-over device and working method thereof
CN112890792A (en) * 2020-11-25 2021-06-04 合肥工业大学 Cloud computing cardiovascular health monitoring system and method based on network camera
CN113627396A (en) * 2021-09-22 2021-11-09 浙江大学 Health monitoring-based skipping rope counting method
CN113876311A (en) * 2021-09-02 2022-01-04 天津大学 Self-adaptively-selected non-contact multi-player heart rate efficient extraction device
CN116999044A (en) * 2023-09-07 2023-11-07 南京云思创智信息科技有限公司 Real-time motion full-connection bidirectional consistent optical flow field heart rate signal extraction method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104138254A (en) * 2013-05-10 2014-11-12 天津点康科技有限公司 Non-contact type automatic heart rate measurement system and measurement method
CN104173051A (en) * 2013-05-28 2014-12-03 天津点康科技有限公司 Automatic noncontact respiration assessing system and assessing method
CN104337509A (en) * 2013-07-26 2015-02-11 塔塔咨询服务有限公司 Measurement of physiological parameter
CN104866805A (en) * 2014-02-20 2015-08-26 腾讯科技（深圳）有限公司 Real-time face tracking method and device
US20160113521A1 (en) * 2014-10-25 2016-04-28 ARC Devices, Ltd Hand-held medical-data capture-device having detection of body core temperature by a microprocessor from a digital infrared sensor having only digital readout ports and having variation amplification and having interoperation with electronic medical record systems
CN105930808A (en) * 2016-04-26 2016-09-07 南京信息工程大学 Moving object tracking method based on vector boosting template updating

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104138254A (en) * 2013-05-10 2014-11-12 天津点康科技有限公司 Non-contact type automatic heart rate measurement system and measurement method
CN104173051A (en) * 2013-05-28 2014-12-03 天津点康科技有限公司 Automatic noncontact respiration assessing system and assessing method
CN104337509A (en) * 2013-07-26 2015-02-11 塔塔咨询服务有限公司 Measurement of physiological parameter
CN104866805A (en) * 2014-02-20 2015-08-26 腾讯科技（深圳）有限公司 Real-time face tracking method and device
US20160113521A1 (en) * 2014-10-25 2016-04-28 ARC Devices, Ltd Hand-held medical-data capture-device having detection of body core temperature by a microprocessor from a digital infrared sensor having only digital readout ports and having variation amplification and having interoperation with electronic medical record systems
CN105930808A (en) * 2016-04-26 2016-09-07 南京信息工程大学 Moving object tracking method based on vector boosting template updating

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
KAIHUA ZHANG ET.AL: ""Fast Compressive Tracking"", 《IEEE》 *

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107330945A (en) * 2017-07-05 2017-11-07 合肥工业大学 A kind of examing heartbeat fastly method based on video
CN107334469A (en) * 2017-07-24 2017-11-10 北京理工大学 Non-contact more people's method for measuring heart rate and device based on SVMs
CN107506716A (en) * 2017-08-17 2017-12-22 华东师范大学 A kind of contactless real-time method for measuring heart rate based on video image
CN109871115A (en) * 2017-12-04 2019-06-11 腾讯科技（深圳）有限公司 Control method, device and computer readable storage medium in multimedia interactive
CN109871115B (en) * 2017-12-04 2021-09-17 腾讯科技（深圳）有限公司 Control method, device and computer readable storage medium in multimedia interaction
GB2572961A (en) * 2018-04-16 2019-10-23 Clinicco Ltd System for vital sign detection from a video stream
CN110393513A (en) * 2018-04-25 2019-11-01 财团法人交大思源基金会 Contactless heartbeat measurement system, method and device thereof
CN109009052A (en) * 2018-07-02 2018-12-18 南京工程学院 The embedded heart rate measurement system and its measurement method of view-based access control model
CN109259748A (en) * 2018-08-17 2019-01-25 西安电子科技大学 The system and method for handset processes face video extraction heart rate signal
CN109480808A (en) * 2018-09-27 2019-03-19 深圳市君利信达科技有限公司 A kind of heart rate detection method based on PPG, system, equipment and storage medium
CN111281367A (en) * 2018-12-10 2020-06-16 绍兴图聚光电科技有限公司 Anti-interference non-contact heart rate detection method based on face video
CN110276271A (en) * 2019-05-30 2019-09-24 福建工程学院 Merge the non-contact heart rate estimation technique of IPPG and depth information anti-noise jamming
CN110866498B (en) * 2019-11-15 2021-07-13 北京华宇信息技术有限公司 Heart rate monitoring method
CN110866498A (en) * 2019-11-15 2020-03-06 北京华宇信息技术有限公司 Portable heart rate monitoring device and heart rate monitoring method thereof
CN111540169A (en) * 2020-04-24 2020-08-14 重庆城市管理职业学院 Bus danger alarm method and system based on intelligent behavior monitoring
CN112890792A (en) * 2020-11-25 2021-06-04 合肥工业大学 Cloud computing cardiovascular health monitoring system and method based on network camera
CN112797840A (en) * 2021-01-28 2021-05-14 杭州屹道科技有限公司 Firearm handing-over device and working method thereof
CN112797840B (en) * 2021-01-28 2023-03-10 杭州屹道科技有限公司 Firearm handing-over device and working method thereof
CN113876311A (en) * 2021-09-02 2022-01-04 天津大学 Self-adaptively-selected non-contact multi-player heart rate efficient extraction device
CN113876311B (en) * 2021-09-02 2023-09-15 天津大学 Non-contact type multi-player heart rate efficient extraction device capable of adaptively selecting
CN113627396A (en) * 2021-09-22 2021-11-09 浙江大学 Health monitoring-based skipping rope counting method
CN113627396B (en) * 2021-09-22 2023-09-05 浙江大学 Rope skipping counting method based on health monitoring
CN116999044A (en) * 2023-09-07 2023-11-07 南京云思创智信息科技有限公司 Real-time motion full-connection bidirectional consistent optical flow field heart rate signal extraction method
CN116999044B (en) * 2023-09-07 2024-04-16 南京云思创智信息科技有限公司 Real-time motion full-connection bidirectional consistent optical flow field heart rate signal extraction method

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