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Optical measurements based on practical methods for detecting time-wise morphing structures
摘要： Nowadays non-contact measurement methods have become widely used systems in several fields especially robotics, aerospace, architecture, and cultural heritage. Practical devices, taken from mass markets, are increasingly being used in scientific and engineering research fields thanks to their ability to combine good accuracy with to the low-cost and ready-to-use experimental setup. In the present paper, digital image analysis (based on digital camera devices) and three-dimensional scanning technique (based on Kinect I and Kinect II sensors) are compared to evaluate their performance in detecting a time-wise shape modification. Digital camera and Kinect sensors are used to the non-contact detection of a morphing blade able to modify its geometry according to airflow temperature variation. The comparison showed the capability of the digital image technique to provide quantitative information when a proper alignment is adopted, while the three-dimensional scanning process allows the continuous blade detection useful to quantify the shape modification. Two-dimensional and three-dimensional blade shape reconstruction processes are also discussed.
关键词： Reverse Engineering,Non-contact measurement,Point cloud,Kinect sensor,Optical method,Digital image analysis
更新于2025-09-23 15:23:52
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[ACM Press the 5th international Workshop - Berlin, Germany (2018.09.20-2018.09.21)] Proceedings of the 5th international Workshop on Sensor-based Activity Recognition and Interaction - iWOAR '18 - Respiration Rate Estimation with Depth Cameras
摘要： Depth cameras have been known to be capable of picking up the small changes in distance from users’ torsos, to estimate respiration rate. Several studies have shown that under certain conditions, the respiration rate from a non-mobile user facing the camera can be accurately estimated from parts of the depth data. It is however to date not clear, what factors might hinder the application of this technology in any setting, what areas of the torso need to be observed, and how readings are affected for persons at larger distances from the RGB-D camera. In this paper, we present a benchmark dataset that consists of the point cloud data from a depth camera, which monitors 7 volunteers at variable distances, for variable methods to pin-point the person’s torso, and at variable breathing rates. Our findings show that the respiration signal’s signal-to-noise ratio becomes debilitating as the distance to the person approaches 4 metres, and that bigger windows over the person’s chest work particularly well. The sampling rate of the depth camera was also found to impact the signal’s quality significantly.
关键词： ToF sensing,Kinect v2,respiratory rate,respiration measurement,non-contact measurement
更新于2025-09-23 15:21:01
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Infrared Camera-Based Non-contact Measurement of Brain Activity From Pupillary Rhythms
摘要： Pupillary responses are associated with affective processing, cognitive function, perception, memory, attention, and other brain activities involving neural pathways. The present study aimed to develop a noncontact system to measure brain activity based on pupillary rhythms using an infra-red web camera. Electroencephalogram (EEG) signals and pupil imaging of 70 undergraduate volunteers (35 female, 35 male) were measured in response to sound stimuli designed to evoke arousal, relaxation, happiness, sadness, or neutral responses. This study successfully developed a real-time system that could detect an EEG spectral index (relative power: low beta in FP1; mid beta in FP1; SMR in FP1; beta in F3; high beta in F8; gamma P4; mu in C4) from pupillary rhythms using the synchronization phenomenon in harmonic frequency (1/100 f) between the pupil and brain oscillations. This method was effective in measuring and evaluating brain activity using a simple, low-cost, noncontact system, and may be an alternative to previous methods used to evaluate brain activity.
关键词： harmonic frequency,pupil size variation,brain activity,vital sign monitoring,non-contact measurement
更新于2025-09-23 15:21:01