0000000000340936
AUTHOR
Mohamed Abul Hassan
showing 4 related works from this author
Evaluation Metric for Rate of Background Detection
2016
International audience; This paper proposes an evaluation metric which derive the effectiveness of background modeling algorithms. Background modeling is a key process on developing visual surveillance systems. The requirement of adapting to dynamic environments has motivated researchers to modify existing background modeling algorithms and develop new algorithms with better adaptability. Having the algorithms developed, credentials of each of the algorithms have to be assessed to exploit their effectiveness. Various evaluation metrics have been used for evaluating the rate of foreground extraction, foreground detection, and overall accuracy. However, the rate of background detection has no…
Video-Based Heartbeat Rate Measuring Method Using Ballistocardiography
2017
International audience; Video-based heartbeat rate measurement is a rapidly growing application in remote health monitoring. Video-based heartbeat rate measuring methods operate mainly by estimating photoplethysmography or ballistocardiography signals. These methods operate by estimating the microscopic color change in the face or by estimating the microscopic rigid motion of the head/facial skin. However, the robustness to motion artifacts caused by illumination variance and motion variance of the subject poses main challenge. We present a video-based heartbeat rate measuring framework to overcome these problems by using the principle of ballistocardiography. In this paper, we proposed a b…
Effect of Motion Artifact on Digital Camera Based Heart Rate Measurement
2017
International audience; Depression is one of the most prevalent mental disorders, burdening many people world-wide. A system with the potential of serving as a decision support system is proposed, based on novel features extracted from facial expression geometry and speech, by interpreting non-verbal manifestations of depression. The proposed system has been tested both in gender independent and gender based modes, and with different fusion methods. The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. The proposed framework achieved a precision of 94.8% for detecting p…
Optimal Source Selection for Image Photoplethysmography
2016
International audience; This paper presents an optimal selection on the region of interest (ROI) and color spaces to extract photoplethysmography signals from facial videos. The study is carried out under two sections; ROI selection and color space selection. We compared five different ROI selection for different regions of the face. We also investigated three color spectrums namely additive, perceptual and orthogonal color spaces. The study experimented on the publicly available human-computer interaction (HCI) database. When evaluated on 30 subjects, the results showed that the ROI selection on the forehead and the green spectrum of the additive color space to provides higher accuracy for…