Remote Heart Rate Measurement from Face Videos under Realistic Situations

Li, Xiaobai; Chen, Jie; Zhao, Guoying; Pietikäinen, Matti

doi:10.1109/cvpr.2014.543

Cited by 455 publications

(419 citation statements)

References 14 publications

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“…This is because of the contamination of heartbeat information by the other lighting and motion sources, which the HP filter alone cannot restore for visibility. Previous methods in [4], [5], [8], [12], [14], [19] moved to the frequency domain and filtered the signal by different bandpass filters and/or calculating the power spectrum of the signal to determine the HR in the frequency domain. However, this cannot provide a heartbeat signal with visible peaks, i.e.…”

Section: Emd-based Signal Decomposition For the Proposed Hpl Estimationmentioning

confidence: 99%

“…Along with the proposed EMD-based method, the applications of color information for HR estimation were shown in [4], [5], [8], [9], [19], and the applications of motion information were shown in [12], [14]. None of these adfa, p. 7, 2011.…”

Section: Hr Calculation Using the Proposed Multi-modal Fusionmentioning

confidence: 99%

“…In order to overcome such problems and show the competency of our methods, we used the publicly available MAHNOB-HCI database [20] for the experiment. The database is recorded in realistic Human-Computer Interaction (HCI) scenarios which was treated as a realistic and highly challenging dataset in the literature [8] because it contains facial videos recorded in realistic scenarios, including challenges from illumination variation and internal and external head motions. It contains videos of 491 sessions with 25 subjects that are longer than 30 seconds, and subjects who consent attribute 'YES'.…”

Section: Experimental Environmentmentioning

confidence: 99%

“…Wei performance than the ICA-based method [6], [7]. Other articles contributed a peripheral improvement of the color-based HR measurement by using a better estimation of ROI [8], adding a supervised machine learning component to the system [9], analyzing the distance between the camera and the face during data capture [10], and selecting best facial patches using majority voting [11].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, an important vital sign, heartbeat rate variability, cannot be obtained without locating heartbeat peaks in the signal. However, employing frequency domain decompositions along with some filters on the extracted color or motion traces from the facial video, as used in state-of-the-art methods of [4], [5], [8], [12], [14], [18], [19], does not provide visible HPLs for further analysis. ii.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Estimation of Heartbeat Peak Locations and Heartbeat Rate from Facial Video

2017

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Section: Emd-based Signal Decomposition For the Proposed Hpl Estimationmentioning

confidence: 99%

Section: Hr Calculation Using the Proposed Multi-modal Fusionmentioning

confidence: 99%

Section: Experimental Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Heartbeat Peak Locations and Heartbeat Rate from Facial Video

2017

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Recent Progress of Optical Imaging Approaches for Noncontact Physiological Signal Measurement: A Review

Zhang

et al. 2023

Advanced Intelligent Systems

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In recent years, optical imaging techniques have gained wide recognition for the measurement of vital signals, such as heart rate, respiratory rate, oxygen saturation, and blood pressure, which are crucial indicators for evaluating human health conditions in clinical examinations. There is a wide range of optical imaging methods for remote physiological signal monitoring, including RGB imaging, thermal imaging, hyperspectral imaging, depth imaging, and multimodal imaging, which provide spatial information compared to other noncontact measurement approaches, thereby allowing extensive applications in this area. In this survey, some fundamental knowledge about optical imaging methods for vital signal measurement is reviewed, including principles of various optical imaging techniques, processing methods for data analysis, discussion on advantages and disadvantages, application summary, and future prospects. This is a comprehensive overview of the noncontact physiological signal measurement of optical imaging approaches.

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A semi‐active human digital twin model for detecting severity of carotid stenoses from head vibration—A coupled computational mechanics and computer vision method

Chakshu

Carson

Sazonov

et al. 2019

Numer Methods Biomed Eng

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In this work, we propose a methodology to detect the severity of carotid stenosis from a video of a human face with the help of a coupled blood flow and head vibration model. This semi‐active digital twin model is an attempt to link noninvasive video of a patient face to the percentage of carotid occlusion. The pulsatile nature of blood flow through the carotid arteries induces a subtle head vibration. This vibration is a potential indicator of carotid stenosis severity, and it is exploited in the present study. A head vibration model has been proposed in the present work that is linked to the forces generated by blood flow with or without occlusion. The model is used to generate a large number of virtual head vibration data for different degrees of occlusion. In order to determine the in vivo head vibration, a computer vision algorithm is adopted to use human face videos. The in vivo vibrations are compared against the virtual vibration data generated from the coupled computational blood flow/vibration model. A comparison of the in vivo vibration is made against the virtual data to find the best fit between in vivo and virtual data. The preliminary results on healthy subjects and a patient clearly indicate that the model is accurate and it possesses the potential for detecting approximate severity of carotid artery stenoses.

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Remote Heart Rate Measurement from Face Videos under Realistic Situations

Cited by 455 publications

References 14 publications

Estimation of Heartbeat Peak Locations and Heartbeat Rate from Facial Video

Estimation of Heartbeat Peak Locations and Heartbeat Rate from Facial Video

Recent Progress of Optical Imaging Approaches for Noncontact Physiological Signal Measurement: A Review

A semi‐active human digital twin model for detecting severity of carotid stenoses from head vibration—A coupled computational mechanics and computer vision method

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