Abstract: Examples disclosed herein are relevant to systems, methods, and other technology for determining furniture compatibility. For example, graph neural networks (GNNs) that leverage relational information between furniture items in a set may be used as models to predict a compatibility score indicative of visual compatibility of furniture items across the set. In one implementation, the GNN-based model can extend the concept of a siamese network to multiple inputs and branches and use a generalized contrastive loss function. In another implementation, the GNN-based model learns both an edge function and the function that generates the compatibility score. The predicted compatibility score can be used for a variety of purposes, including furniture item recommendations.

Abstract: Examples disclosed herein are relevant to systems, methods, and other technology for determining furniture compatibility. For example, graph neural networks (GNNs) that leverage relational information between furniture items in a set may be used as models to predict a compatibility score indicative of visual compatibility of furniture items across the set. In one implementation, the GNN-based model can extend the concept of a siamese network to multiple inputs and branches and use a generalized contrastive loss function. In another implementation, the GNN-based model learns both an edge function and the function that generates the compatibility score. The predicted compatibility score can be used for a variety of purposes, including furniture item recommendations.

Abstract: A method, non-transitory computer readable medium and apparatus for generating graphical chromophore maps are disclosed. For example, the method includes receiving an image of a customer from a mobile endpoint device of the customer, wherein the image is taken via the mobile endpoint device of the customer, converting RGB values of the image into a spectral representation, performing a constrained independent component analysis (ICA) on the spectral representation to obtain three or more independent components that are ordered, generating a first graphical chromophore map of a first independent component of the three or more independent components that are ordered and a second graphical chromophore map of a second independent component of the three or more independent components that are ordered and transmitting the first graphical chromophore map and the second graphical chromophore map to the mobile endpoint device of the customer for display.

Abstract: A method, non-transitory computer readable medium and apparatus for generating one or more graphical chromophore maps are disclosed. For example, the method includes receiving a plurality of images from a plurality of different customers, estimating a plurality of different illuminates that were used to capture each one of the plurality of images, calculating a correlation of a spectral reflectance of a lip region of a customer with an absorption curve of hemoglobin for the each one of the plurality of images for each one of the plurality of different illuminates that is estimated, selecting an illuminance of the plurality of different illuminates that provides a highest correlation and generating one or more graphical chromophore maps for subsequently received images of customers using the illuminance that is selected.

Abstract: A method, non-transitory computer readable medium and apparatus for transmitting an assessment of facial skin health of a customer are disclosed. For example, the method includes receiving an image of a customer from a mobile endpoint device of the customer, analyzing one or more parameters of a facial skin of the customer in the image of the customer, determining the assessment of facial skin health of the customer based on the one or more parameters of the facial skin that are analyzed and transmitting the assessment of facial skin health to the mobile endpoint device of the customer to cause the mobile endpoint device to automatically display the assessment of facial skin health.

Abstract: A method, non-transitory computer readable medium and apparatus for generating an interactive image of facial skin of a user that is displayed via a mobile endpoint device of the user are disclosed. For example, the method includes displaying a guide to position a face of the user, capturing an image of the face of the user, transmitting the image to a facial skin analysis server for analyzing one or more parameters of the facial skin of the user, receiving the interactive image of the face of the user that includes metadata associated with the one or more parameters of the facial skin that were analyzed by the facial skin analysis server, and displaying the interactive image of the face of the user.

Abstract: A method, non-transitory computer readable medium and apparatus for generating one or more graphical chromophore maps are disclosed. For example, the method includes receiving a plurality of images from a plurality of different customers, estimating a plurality of different illuminates that were used to capture each one of the plurality of images, calculating a correlation of a spectral reflectance of a lip region of a customer with an absorption curve of hemoglobin for the each one of the plurality of images for each one of the plurality of different illuminates that is estimated, selecting an illuminance of the plurality of different illuminates that provides a highest correlation and generating one or more graphical chromophore maps for subsequently received images of customers using the illuminance that is selected.

Abstract: A method, non-transitory computer readable medium and apparatus for generating graphical chromophore maps are disclosed. For example, the method includes receiving an image of a customer from a mobile endpoint device of the customer, wherein the image is taken via the mobile endpoint device of the customer, converting RGB values of the image into a spectral representation, performing a constrained independent component analysis (ICA) on the spectral representation to obtain three or more independent components that are ordered, generating a first graphical chromophore map of a first independent component of the three or more independent components that are ordered and a second graphical chromophore map of a second independent component of the three or more independent components that are ordered and transmitting the first graphical chromophore map and the second graphical chromophore map to the mobile endpoint device of the customer for display.

Abstract: A method, non-transitory computer readable medium and apparatus for transmitting an assessment of facial skin health of a customer are disclosed. For example, the method includes receiving an image of a customer from a mobile endpoint device of the customer, analyzing one or more parameters of a facial skin of the customer in the image of the customer, determining the assessment of facial skin health of the customer based on the one or more parameters of the facial skin that are analyzed and transmitting the assessment of facial skin health to the mobile endpoint device of the customer to cause the mobile endpoint device to automatically display the assessment of facial skin health.

Abstract: A method, non-transitory computer readable medium and apparatus for generating an interactive image of facial skin of a user that is displayed via a mobile endpoint device of the user are disclosed. For example, the method includes displaying a guide to position a face of the user, capturing an image of the face of the user, transmitting the image to a facial skin analysis server for analyzing one or more parameters of the facial skin of the user, receiving the interactive image of the face of the user that includes metadata associated with the one or more parameters of the facial skin that were analyzed by the facial skin analysis server, and displaying the interactive image of the face of the user.

Abstract: What is disclosed is a system and method for classifying a time-series signal as ventricular premature contraction in a subject being monitored for cardiac function assessment. One embodiment hereof involves first, receive a time-series signal which contains frequency components that relate to the function of the subject's heart. Signal segments of interest are identified in the time-series signal. Time-domain features comprising the peak-to-peak interval between cardiac pulses and pulse amplitudes are extracted for each signal segment of interest. The time-domain features are arranged into a two dimensional feature vector. Each feature vector is associated with a respective signal segment. A magnitude of each signal segment's respective feature vector is determined. Signal segments are classified as being ventricular premature contraction based on each segment's associated magnitude.

Abstract: What is disclosed is a system and method for assessing risk for ventricular tachycardia from a time-series signal of a patient monitored for cardiac function assessment. One embodiment involves receiving a time-series signal which contains frequency components that relate to the function of the subject's heart. Signal segments of interest are identified in the time-series signal. Time-domain features are extracted for each signal segment of interest. The time-domain features are arranged into a two dimensional feature vector. Each feature vector is associated with a respective signal segment. A magnitude of each signal segment's respective feature vector is determined. Signal segments are classified as being ventricular premature contraction based on each segment's associated magnitude.

Abstract: What is disclosed is a system and method for classifying a time-series signal as being ventricular premature contraction, ventricular tachycardia, or normal sinus rhythm in a patient being monitored for cardiac function assessment. One embodiment hereof involves the following. A time-series signal is received which contains frequency components that relate to the function of the subject's heart. Signal segments of interest are identified in the time-series signal. Time-domain features, frequency-domain features, and non-linear cardiac dynamics are extracted from each of the identified signal segments of interest. The extracted features and dynamics become components of at least one feature vector associated with each respective signal segment of interest. Signal segments are then classified as one of: ventricular premature contraction, ventricular tachycardia, and normal sinus rhythm, based on each signal segment's respective feature vector(s).