Comparison between the Kinect™ V1 and Kinect™ V2 for respiratory motion tracking

Samir, Mohammed; Golkar, Ehsan; Rahni, Ashrani Aizzuddin Abd

doi:10.1109/icsipa.2015.7412180

Cited by 24 publications

(16 citation statements)

References 4 publications

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“…The next generation of Kinect sensor (Kinect v2) released in 2014 has advantages over the original Kinect technology in terms of performance, accuracy and wide field of view [42,43,44,45]. This is because the Kinect v2 uses a ToF technology [46] for the depth measurements instead of the structured light coding technology [47] used in Kinect v1.…”

Section: Kinect Sensormentioning

confidence: 99%

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

Al-Naji

Gibson

Lee

et al. 2017

Sensors

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Abstract:The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications.

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Section: Kinect Sensormentioning

confidence: 99%

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

Al-Naji

Gibson

Lee

et al. 2017

Sensors

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“…The reported results confirm that the latter has higher accuracy and lesser noise under controlled lighting conditions. In the work of Samir [10], the MS Kinect v1 and v2 are evaluated for tracking the breathing (respiratory) movement in humans. The results show that the accuracy of v2 is slightly better than v1.…”

Section: Comparison Of Sensors For 3d Visionmentioning

confidence: 99%

A Generic Approach for Error Estimation of Depth Data from (Stereo and RGB-D) 3D Sensors

Fernández¹,

Ávila²,

Gonçalves³

2017

Preprint

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Abstract:We propose an approach for estimating the error in depth data provided by generic 3D sensors, which are modern devices capable of generating an image (RGB data) and a depth map (distance) or other similar 2.5D structure (e.g. stereo disparity) of the scene. Our approach starts capturing images of a checkerboard pattern devised for the method. Then proceed with the construction of a dense depth map using functions that generally comes with the device SDK (based on disparity or depth). The 2D processing of RGB data is performed next to find the checkerboard corners. Clouds of corner points are finally created (in 3D), over which an RMS error estimation is computed. We come up with a multi-platform system and its verification and evaluation has been done, using the development kit of the board nVIDIA Jetson TK1 with the MS Kinects v1/v2 and the Stereolabs ZED camera. So the main contribution is the error determination procedure that does not need any data set or benchmark, thus relying only on data acquired on-the-fly. With a simple checkerboard, our approach is able to determine the error for any device. Envisioned application is on 3D reconstruction for robotic vision, with a series of 3D vision sensors embarked in robots (UAV of type quadcopter and terrestrial robots) for high-precision map construction, which can be used for sensing and monitoring.

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“…Later, Microsoft developed it to be compatible with Windows using a standard development kit (SDK) and a power conversion adaptor. The next version of the Kinect sensors (Kinect v2) was released in 2014 based on a time of flight (ToF) technology [ 2 ] with improved specifications compared to the original Kinect in terms of regarding to speed, accuracy, and increased field of view [ 3 , 4 , 5 , 6 , 7 ]. The built-in Kinect software library can provide many processing techniques, including body tracking, three-dimensional body reconstruction, face detection, joint tracking, skeletal tracking, and human recognition using the image sequences acquired from three built-in optical sensors: a red, green, and blue (RGB) sensor, infrared (IR) sensor, and depth sensor.…”

Section: Introductionmentioning

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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Comparison between the Kinect™ V1 and Kinect™ V2 for respiratory motion tracking

Cited by 24 publications

References 4 publications

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

A Generic Approach for Error Estimation of Depth Data from (Stereo and RGB-D) 3D Sensors

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

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