Quality index evaluation of videos based on fuzzy interface system

Al-Naji, Ali; Lee, Sang‐Heon; Chahl, Javaan

doi:10.1049/iet-ipr.2016.0569

Cited by 30 publications

(17 citation statements)

References 42 publications

(65 reference statements)

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“…The cardiorespiratory signal derived from the optical properties of skin color changes can be described as the iPPG signal. Head Motion Magnification Based-Method: Based on an efficient motion magnification method [43] , the image sequences of the input video are converted from red green blue (RGB) colour space to YC b C r colour space to separate the color data from the intensity data. Only the Y channel was used and downsized to reduce the processing time.…”

Section: Methods and Proceduresmentioning

confidence: 99%

Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal

Al-Naji

Chahl

2017

IEEE J. Transl. Eng. Health Med.

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Most existing non-contact monitoring systems are limited to detecting physiological signs from a single subject at a time. Still, another challenge facing these systems is that they are prone to noise artifacts resulting from motion of subjects, facial expressions, talking, skin tone, and illumination variations. This paper proposes an efficient non-contact system based on a digital camera to track the cardiorespiratory signal from a number of subjects (up to six persons) at the same time with a new method for noise artifact removal. The proposed system relied on the physiological and physical effects as a result of the activity of the cardiovascular and respiratory systems, such as skin color changes and head motion. Since these effects are imperceptible to the human eye and highly affected by the noise variations, we used advanced signal and video processing techniques, including developing video magnification technique, complete ensemble empirical mode decomposition with adaptive noise, and canonical correlation analysis to extract the heart rate and respiratory rate from multiple subjects under the noise artifact assumptions. The experimental results of the proposed system had a significant correlation (Pearson’s correlation coefficient = 0.9994, Spearman correlation coefficient = 0.9987, and root mean square error = 0.32) when compared with the conventional contact methods (pulse oximeter and piezorespiratory belt), which makes the proposed system a promising candidate for novel applications.

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Section: Methods and Proceduresmentioning

confidence: 99%

Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal

Al-Naji

Chahl

2017

IEEE J. Transl. Eng. Health Med.

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“…The magnification technique proposed in [ 30 ] was used to provide a real-time magnification since this technique has better noise performance and video quality than other magnification techniques. The magnification process was used to either magnify the video data captured by the RGB sensor in a well-lit environment or to magnify the video data captured by the IR sensor in a dark environment, since the RGB sensor is not effective in the dark.…”

Section: Methods and Proceduresmentioning

confidence: 99%

Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor

Al-Naji

Chahl

2018

Sensors

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Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation of cardiopulmonary-signal-and-detection-related abnormal cardiopulmonary events (e.g., tachycardia, bradycardia, tachypnea, bradypnea, and central apnoea) in many possible sleeping postures within varying environmental settings including in total darkness and whether the subject is covered by a blanket or not. The proposed system extracts the signal from the abdominal-thoracic region where cardiopulmonary activity is most pronounced, using a real-time image sequence captured by Kinect v2 sensor. The proposed system shows promising results in any sleep posture, regardless of illumination conditions and unclear ROI even in the presence of a blanket, whilst being reliable, safe, and cost-effective.

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“…In the first step, we used an enhanced video magnification technique [ 27 ] to magnify skin colour variation since the variation caused by the cardiac pulse signal is very weak. Although the digital camera can reveal the iPPG signal, there was substantial noise associated with this signal caused by effecting of illumination variations, subject’s movement and camera movement.…”

Section: Methodsmentioning

confidence: 99%

Remote monitoring of cardiorespiratory signals from a hovering unmanned aerial vehicle

2017

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BackgroundRemote physiological measurement might be very useful for biomedical diagnostics and monitoring. This study presents an efficient method for remotely measuring heart rate and respiratory rate from video captured by a hovering unmanned aerial vehicle (UVA). The proposed method estimates heart rate and respiratory rate based on the acquired signals obtained from video-photoplethysmography that are synchronous with cardiorespiratory activity.MethodsSince the PPG signal is highly affected by the noise variations (illumination variations, subject’s motions and camera movement), we have used advanced signal processing techniques, including complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and canonical correlation analysis (CCA) to remove noise under these assumptions.ResultsTo evaluate the performance and effectiveness of the proposed method, a set of experiments were performed on 15 healthy volunteers in a front-facing position involving motion resulting from both the subject and the UAV under different scenarios and different lighting conditions.ConclusionThe experimental results demonstrated that the proposed system with and without the magnification process achieves robust and accurate readings and have significant correlations compared to a standard pulse oximeter and Piezo respiratory belt. Also, the squared correlation coefficient, root mean square error, and mean error rate yielded by the proposed method with and without the magnification process were significantly better than the state-of-the-art methodologies, including independent component analysis (ICA) and principal component analysis (PCA).

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Quality index evaluation of videos based on fuzzy interface system

Cited by 30 publications

References 42 publications

Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal

Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal

Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor

Remote monitoring of cardiorespiratory signals from a hovering unmanned aerial vehicle

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