Abstract: A system and method compute, store and use relativity measures between events in datasets where the measures are stored in a relational memory for querying. From user data and e-commerce shopping session data, relativity measures are computed for a plurality of subsets of data attributes of the user data and session data, each subset comprising two or more data attributes. The relativity measures individually or when combined represent conditional relativities between a set of events within the session data. Only the relativity measures are stored to the relational memory. The measures may be queried for results and applied to the e-commerce service (e.g. to determine which specific product data to present or an order of the presentation of the specific product data). The relativity measures may be computed only for pre-selected relations between particular data attributes which give desired trends and insights into user shopping using the e-commerce service.

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

Abstract: Systems and methods relate to a network model to apply an effect to an image such as an augmented reality effect (e.g. makeup, hair, nail, etc.). The network model uses a conditional cycle-consistent generative image-to-image translation model to translate images from a first domain space where the effect is not applied and to a second continuous domain space where the effect is applied. In order to render arbitrary effects (e.g. lipsticks) not seen at training time, the effect's space is represented as a continuous domain (e.g. a conditional variable vector) learned by encoding simple swatch images of the effect, such as are available as product swatches, as well as a null effect. The model is trained end-to-end in an unsupervised fashion. To condition a generator of the model, convolutional conditional batch normalization (CCBN) is used to apply the vector encoding the reference swatch images that represent the makeup properties.

Abstract: Disruption of computerized face detection includes receiving a source image that contains a representation of a face and computing a perturbation for the source image. The perturbation is specific to the source image and is configured for a target face detector. A perturbed image is then generated by adding the perturbation to the source image and then the perturbed image may be outputted instead of the source image.

Abstract: A computer-implemented method for correcting a makeup or skin effect to be rendered on a surface region of an image of a portion of a body of a person. The method and system correcting the makeup or skin effect by accounting for image-specific light field parameters, such as a light profile estimate and minimum light field estimation, and rendering the corrected the makeup or skin effect on the image to generate a corrected image.

Abstract: A computer-implemented method for correcting a makeup or skin effect to be rendered on a surface region of an image of a portion of a body of a person. The method and system correcting the makeup or skin effect by accounting for image-specific light field parameters, such as a light profile estimate and minimum light field estimation, and rendering the corrected the makeup or skin effect on the image to generate a corrected image.

Abstract: There is provided a framework including systems and methods for analyzing skin parameters from images or videos showing skin. Using a series of Hierarchical Differential Image Filters (HDIF), it becomes possible to detect different skin features such as wrinkles, spots, and roughness. The hierarchical differential image filter computes two enhancements to an image showing skin at two different levels of enhancement, determines a differential image using the two enhancements and computes the skin analysis rating using the differential image. These skin ratings are comparably accurate to actual ratings by dermatologists.

Abstract: A computer-implemented method for correcting a makeup or skin effect to be rendered on a surface region of an image of a portion of a body of a person. The method and system correcting the makeup or skin effect by accounting for image-specific light field parameters, such as a light profile estimate and minimum light field estimation, and rendering the corrected the makeup or skin effect on the image to generate a corrected image.

Abstract: There is provided a framework including systems and methods for analyzing skin parameters from images or videos showing skin. Using a series of Hierarchical Differential Image Filters (HDIF), it becomes possible to detect different skin features such as wrinkles, spots, and roughness. The hierarchical differential image filter computes two enhancements to an image showing skin at two different levels of enhancement, determines a differential image using the two enhancements and computes the skin analysis rating using the differential image. These skin ratings are comparably accurate to actual ratings by dermatologists.

Abstract: A system and method compute, store and use relativity measures between events in datasets where the measures are stored in a relational memory for querying. From user data and e-commerce shopping session data, relativity measures are computed for a plurality of subsets of data attributes of the user data and session data, each subset comprising two or more data attributes. The relativity measures individually or when combined represent conditional relativities between a set of events within the session data. Only the relativity measures are stored to the relational memory. The measures may be queried for results and applied to the e-commerce service (e.g. to determine which specific product data to present or an order of the presentation of the specific product data). The relativity measures may be computed only for pre-selected relations between particular data attributes which give desired trends and insights into user shopping using the e-commerce service.

Abstract: Provided is a method and system of providing a cosmetics enhancement interface. The method comprises showing, at the display screen of a computing device having a memory and a processor: a digital photograph including facial features; an interactive dialog portion reflecting a conversational input received and a subsequent response provided thereto from the computing device; and a product display portion; receiving an inquiry, as reflected in the interactive dialog portion, related to a cosmetic product for application onto a selected facial feature; receiving a selection of the cosmetic product based on a matching to the at least one facial feature according to a predefined rule; displaying, at the product display portion, a product representation associated with the selected cosmetic product; receiving an update request; and updating the digital photograph showing a modification to the facial feature on the display screen by simulating application of the selected cosmetic product thereon.

Abstract: This document relates to hybrid eye center localization using machine learning, namely cascaded regression and hand-crafted model fitting to improve a computer. There are proposed systems and methods of eye center (iris) detection using a cascade regressor (cascade of regression forests) as well as systems and methods for training a cascaded regressor. For detection, the eyes are detected using a facial feature alignment method. The robustness of localization is improved by using both advanced features and powerful regression machinery. Localization is made more accurate by adding a robust circle fitting post-processing step. Finally, using a simple hand-crafted method for eye center localization, there is provided a method to train the cascaded regressor without the need for manually annotated training data. Evaluation of the approach shows that it achieves state-of-the-art performance.

Abstract: A computer-implemented method for correcting a makeup or skin effect to be rendered on a surface region of an image of a portion of a body of a person. The method and system correcting the makeup or skin effect by accounting for image-specific light field parameters, such as a light profile estimate and minimum light field estimation, and rendering the corrected the makeup or skin effect on the image to generate a corrected image.

Abstract: Computerized method and system for creating a personalized advertisement, and for recommending a product being advertised. An uploaded facial photograph is received, the facial photograph including a plurality of facial features. At least one facial feature of the plurality of facial features is detected. Personal information may be extracted by analyzing the at least one detected facial feature. A product being advertised may be recommended, wherein the recommended product applies to a treatment related to the extracted personal information. A tutorial may indicate on the photograph the facial region to be modified by application of the product, such as to achieve a specific look.

Abstract: Based on a multi-step process, an automatic hair segmentation method and system are disclosed. By extracting various information components from an image, including background color, face position, hair color, skin color, and skin mask, a heuristic-based method is created for the detection and segmentation of hair that can detect hair with an accuracy of approximately 75% and with a false hair overestimation error of 34%. Furthermore, it is shown that down sampling the image down to a face width of 25 px results in a 73% reduction in computation time with insignificant change in detection accuracy.

Abstract: There is provided a framework including systems and methods for analyzing skin parameters from images or videos showing skin. Using a series of Hierarchical Differential Image Filters (HDIF), it becomes possible to detect different skin features such as wrinkles, spots, and roughness. The hierarchical differential image filter computes two enhancements to an image showing skin at two different levels of enhancement, determines a differential image using the two enhancements and computes the skin analysis rating using the differential image. These skin ratings are comparably accurate to actual ratings by dermatologists.

Abstract: The present invention is a method, system and computer prod act operable to receive one or more images and/or video and to utilize such images/video to generate an analysis that is the basis tor recommendations for products and/or treatments provided to a user. The invention generates statistical analysis particular to person shown in the images/video. The statistical information may be displayed to a user. This statistical analysis may be utilized by the invention to generate recommendations for products and/or treatments for the person shown in the images/video. The invention may further generate an image showing the result of an application of a product or treatment to the person shown in the video. The invention may be provided to a user on a computing device, such as, for example as an App on a mobile device.

Abstract: The present invention is a system, method and application for skin health visualization and quantification. The present invention is operable to process an image or video showing skin of a subject to determine characteristics of the skin through a quantitative measuring of parameters. The image or video is processed and analyzed a software application executed by a system incorporating a computer processor, data storage and display unit. A camera may further be integrated system. One or more filters applied to the image or video, to identify characteristics of the skin. A result of skin health results and overall skin health is generated. The image or video, skin health results and/or overall skin health may be displayed to a user. A visualization of amplifications or attenuations of skin health may further be displayed to a user. The invention may be wholly provided in a mobile device.

Abstract: Computerized method and system for creating a personalized advertisement, and for recommending a product being advertised. An uploaded facial photograph is received, the facial photograph including a plurality of facial features. At least one facial feature of the plurality of facial features is detected. Personal information may be extracted by analyzing the at least one detected facial feature. A product being advertised may be recommended, wherein the recommended product applies to a treatment related to the extracted personal information. A tutorial may indicate on the photograph the facial region to be modified by application of the product, such as to achieve a specific look.

Abstract: Based on a multi-step process, an automatic hair segmentation method and system are disclosed. By extracting various information components from an image, including background color, face position, hair color, skin color, and skin mask, a heuristic-based method is created for the detection and segmentation of hair that can detect hair with an accuracy of approximately 75% and with a false hair overestimation error of 34%. Furthermore, it is shown that down sampling the image down to a face width of 25 px results in a 73% reduction in computation time with insignificant change in detection accuracy.