Privacy-Phys: Facial Video-Based Physiological Modification for Privacy Protection

Sun, Zhaodong; Li, Xiaobai

doi:10.1109/lsp.2022.3185964

Cited by 19 publications

(4 citation statements)

References 36 publications

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“…In daily life and work, there is a potential privacy problem with the leakage of physiological information, including physiological signals and facial expressions. Sun and Li [100] presented a new approach based on a pre-trained 3D convolutional neural network, i.e., Privacy-Phys, to modify remote photoplethysmography in facial videos for privacy. The results showed that the approach was more effective and efficient than the previous baseline.…”

Section: Ethical and Privacy Concerns Related To The Use Of Physiolog...mentioning

confidence: 99%

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Lin

2023

Applied Sciences

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People’s emotions play an important part in our daily life and can not only reflect psychological and physical states, but also play a vital role in people’s communication, cognition and decision-making. Variations in people’s emotions induced by external conditions are accompanied by variations in physiological signals that can be measured and identified. People’s psychological signals are mainly measured with electroencephalograms (EEGs), electrodermal activity (EDA), electrocardiograms (ECGs), electromyography (EMG), pulse waves, etc. EEG signals are a comprehensive embodiment of the operation of numerous neurons in the cerebral cortex and can immediately express brain activity. EDA measures the electrical features of skin through skin conductance response, skin potential, skin conductance level or skin potential response. ECG technology uses an electrocardiograph to record changes in electrical activity in each cardiac cycle of the heart from the body surface. EMG is a technique that uses electronic instruments to evaluate and record the electrical activity of muscles, which is usually referred to as myoelectric activity. EEG, EDA, ECG and EMG have been widely used to recognize and judge people’s emotions in various situations. Different physiological signals have their own characteristics and are suitable for different occasions. Therefore, a review of the research work and application of emotion recognition and judgment based on the four physiological signals mentioned above is offered. The content covers the technologies adopted, the objects of application and the effects achieved. Finally, the application scenarios for different physiological signals are compared, and issues for attention are explored to provide reference and a basis for further investigation.

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Section: Ethical and Privacy Concerns Related To The Use Of Physiolog...mentioning

confidence: 99%

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Lin

2023

Applied Sciences

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“…For example, in PulseEdit [88], a novel security algorithm capable of editing physiological signals to conceal a person's cardiac activity and physiological status without altering or distorting the original visual appearance was proposed to protect the user's physiological signal from being disclosed. Similarly, Sun et al [89] proposed PrivacyPhys, a model that modifies rPPG in facial videos captured from online video meetings or video-sharing platforms in order to safeguard against malicious capture and ensure privacy.…”

Section: Gaps and Influencing Challengesmentioning

confidence: 99%

Review on remote heart rate measurements using photoplethysmography

Lee,

Sivakumar,

Lim

2023

Multimed Tools Appl

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Remote photoplethysmography (rPPG) gains recent great interest due to its potential in contactless heart rate measurement using consumer-level cameras. This paper presents a detailed review of rPPG measurement using computer vision and deep learning techniques for heart rate estimation. Several common gaps and difficulties of rPPG development are highlighted for the feasibility study in real-world applications. Numerous computer vision and deep learning methods are reviewed to mitigate crucial issues such as motion artifact and illumination variation. In comparison, deep learning approaches are proven more accurate than conventional computer vision methods due to their adaptive pattern learning and generalization characteristics. An increasing trend of applying deep learning techniques in rPPG can improve effective heart rate estimation and artifact removal. To consider more realistic disturbances into account, additional vital signs and large training datasets are crucial to improve the accuracy of heart rate estimations. By taking the benefit of contactless and accurate estimation, the application of rPPG can be greatly adopted in real-world activities, especially in precision sports.

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“…[ 123 ] But it was only tested on simple datasets, which may be not suitable for realistic situations such as sudden facial expressions. To address the aforementioned problems, Sun et al [ 124 ] presented a novel method called Privacy‐Phys on the basis of a pretrained 3D convolutional neural network, to modify rPPG signal in facial videos, in which the modified video is visibly similar to the original video. Future works should pay more attention to privacy‐preserving techniques for personal information protection.…”

Section: Future Prospectsmentioning

confidence: 99%

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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Privacy-Phys: Facial Video-Based Physiological Modification for Privacy Protection

Cited by 19 publications

References 36 publications

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Review on remote heart rate measurements using photoplethysmography

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

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