Abstract: What is disclosed is a system for compensating for motion induced artifacts in a physiological signal obtained from multiple videos of a first and second region of interest a subject being monitored for a desired physiological function. At least one of the videos being of the first region and at least one of the videos being of the second region. The first region being at least one area of exposed skin where a desired signal corresponding to the physiological function can be registered by a video imaging device. The second region being an area where a movement by the subject is likely to induce motion artifacts into the signal. The videos are processed to isolate pixels associated with the first and second regions. Processed pixels of the isolated first regions to obtain a composite time-series signal. From the composite signal, a physiological signal corresponding to the physiological function is extracted.

Abstract: What is disclosed is a system and method for compensating for motion induce artifacts in a physiological signal obtained from a video. In one embodiment, a video of a first and second region of interest of a subject being monitored for a desired physiological function is captured by a video device. The first region is an area of exposed skin wherein a desired signal corresponding to the physiological function can be registered. The second region is an area where movement is likely to induce motion artifacts into that signal. The video is processed to isolate pixels in the image frames associated with these regions. Pixels of the first region are processed to obtain a time-series signal. A physiological signal is extracted from the time-series signal. Pixels of the second region are analyzed to identify motion. The physiological signal is processed to compensate for the identified motion.

Abstract: What is disclosed is a system and method for processing a video for respiratory function analysis. In one embodiment, a video is received of a region of the subject's body where a time-varying signal corresponding to the subject's respiration can be registered by the video camera. Pixels in a first batch of frames are processed to obtain a time-series signal which is filtered using a band-pass filter with a low and high cutoff frequency fL and fH, where fL and fH are a function of the subject's tidal breathing. The filtered time-series signal is analyzed to identify a next low and high cutoff frequency f?L and F?H, where fL<f?L and f?H<fH. Thereafter, next successive batch of frames are repeatedly processed to obtain respective next time-series signal which is filtered using a band-pass filter with the cutoff frequency f?L and f?H. The filtered signals are processed to obtain a respiratory signal.

Abstract: What is disclosed is a system and method for enhancing a spatio-temporal resolution of a depth data stream. In one embodiment, time-sequential reflectance frames and time-sequential depth frames of a scene are received. If a temporal resolution of the reflectance frames is greater than the depth frames then a new depth frame is generated based on correlations determined between motion patterns in the sequence of reflectance frames and the sequence of depth frames. The new depth frame is inserted into the sequence of depth frames at a selected time point. If a spatial resolution of the reflectance frames is greater than the depth frames then the spatial resolution of a selected depth frame is enhanced by generating new pixel depth values which are added to the selected depth frame. The spatially enhanced depth frame is then inserted back into the sequence of depth frames.

Abstract: What is disclosed is a system and method for identifying a patient's breathing pattern for respiratory function assessment without contact and with a depth-capable imaging system. In one embodiment, a time-varying sequence of depth maps are received of a target region of a subject of interest over a period of inspiration and expiration. Once received, the depth maps are processed to obtain a breathing signal for the subject. The subject's breathing signal comprises a temporal sequence of instantaneous volumes. One or more segments of the subject's breathing signal are then compared against one or more reference breathing signals each associated with a known pattern of breathing. As a result of the comparison, a breathing pattern for the subject is identified. The identified breathing pattern is then used to assess the subject's respiratory function. The teachings hereof find their uses in an array of diverse medical applications. Various embodiments are disclosed.

Abstract: What is disclosed is a system and method for generating a flow-volume loop for respiratory function assessment of a subject of interest in a non-contact, remote sensing environment. In one embodiment, a time-varying sequence of depth maps of a target region of a subject of interest being monitored for respiratory function is received. The depth maps are of that target region over a period of inspiration and expiration. The depth maps are processed to obtain a volume signal comprising a temporal sequence of instantaneous volumes. The time-varying volume signal is processed to obtain a flow-volume loop. Changes in a contour of the flow-volume loop are used to assess the subject's respiratory function. The teachings hereof find their uses in a wide array of medical applications where it is desired to monitor respiratory function of patients such as elderly patients, chronically ill patients with respiratory diseases and premature babies.

Abstract: What is disclosed is a video-based system and method for estimating heart rate variability from time-series signals generated from video images captured of a subject of interest being monitored for cardiac function. In a manner more fully disclosed herein, low frequency and high frequency components are extracted from a time-series signal obtained by processing a video of the subject being monitored. A ratio of the low and high frequency of the integrated power spectrum within these components is computed. Analysis of the dynamics of this ratio over time is used to estimate heart rate variability. The teachings hereof can be used in a continuous monitoring mode with a relatively high degree of measurement accuracy and find their uses in a variety of diverse applications such as, for instance, emergency rooms, cardiac intensive care units, neonatal intensive care units, and various telemedicine applications.

Abstract: What is disclosed is a video system and method that accounts for differences in imaging characteristics of differing video systems used to acquire video of respective regions of interest of a subject being monitored for a desired physiological function. In one embodiment, video is captured using N video imaging devices, where N?2, of respective regions of interest of a subject being monitored for a desired physiological function (i.e., a respiratory or cardiac function). Each video imaging device is different but has complimentary imaging characteristics. A reliability factor f is determined for each of the devices in a manner more fully disclosed herein. A time-series signal is generated from each of the videos. Each time-series signal is weighted by each respective reliability factor and combined to obtain a composite signal. A physiological signal can be then extracted from the composite signal. The processed physiological signal corresponds to the desired physiological function.

Abstract: What is disclosed is a system for compensating for motion induced artifacts in a physiological signal obtained from multiple videos of a first and second region of interest a subject being monitored for a desired physiological function. At least one of the videos being of the first region and at least one of the videos being of the second region. The first region being at least one area of exposed skin where a desired signal corresponding to the physiological function can be registered by a video imaging device. The second region being an area where a movement by the subject is likely to induce motion artifacts into the signal. The videos are processed to isolate pixels associated with the first and second regions. Processed pixels of the isolated first regions to obtain a composite time-series signal. From the composite signal, a physiological signal corresponding to the physiological function is extracted.

Abstract: What is disclosed is a system and method for compensating for motion induce artifacts in a physiological signal obtained from a video. In one embodiment, a video of a first and second region of interest of a subject being monitored for a desired physiological function is captured by a video device. The first region is an area of exposed skin wherein a desired signal corresponding to the physiological function can be registered. The second region is an area where movement is likely to induce motion artifacts into that signal. The video is processed to isolate pixels in the image frames associated with these regions. Pixels of the first region are processed to obtain a time-series signal. A physiological signal is extracted from the time-series signal. Pixels of the second region are analyzed to identify motion. The physiological signal is processed to compensate for the identified motion.

Abstract: A method for processing black point compensation parameters for a color image to be printed so as to enhance image quality of the color image is provided. The method includes converting a received color image to a gray scale image; determining, using the received color image and the gray scale image, a performance attribute to estimate the effect of the black point compensation parameters on the image quality of the received color image, respectively; deriving a model to estimate relationships between the black point compensation parameters and the determined performance attribute; maximizing the performance attribute of the derived model so as to process the black point compensation parameters for the color image; and using the processed black point compensation parameters to construct output device profiles.

Abstract: A method for processing black point compensation parameters for a color image to be printed so as to enhance image quality of the color image is provided.

Abstract: A method for processing black point compensation parameters for a color image to be printed so as to enhance image quality of the color image is provided. The method includes converting a received color image to a gray scale image; determining, using the received color image and the gray scale image, a performance attribute to estimate the effect of the black point compensation parameters on the image quality of the received color image, respectively; deriving a model to estimate relationships between the black point compensation parameters and the determined performance attribute; maximizing the performance attribute of the derived model so as to process the black point compensation parameters for the color image; and using the processed black point compensation parameters to construct output device profiles.

Abstract: A method for processing black point compensation parameters for a color image to be printed so as to enhance image quality of the color image is provided.

Abstract: What is disclosed is a video-based system and method for estimating heart rate variability from time-series signals generated from video images captured of a subject of interest being monitored for cardiac function. In a manner more fully disclosed herein, low frequency and high frequency components are extracted from a time-series signal obtained by processing a video of the subject being monitored. A ratio of the low and high frequency of the integrated power spectrum within these components is computed. Analysis of the dynamics of this ratio over time is used to estimate heart rate variability. The teachings hereof can be used in a continuous monitoring mode with a relatively high degree of measurement accuracy and find their uses in a variety of diverse applications such as, for instance, emergency rooms, cardiac intensive care units, neonatal intensive care units, and various telemedicine applications.