Abstract: Methods, devices, and systems for expression transfer are disclosed. The disclosure includes capturing a first image of a face of a person. The disclosure includes generating an avatar based on the first image of the face of the person, with the avatar approximating the first image of the face of the person. The disclosure includes transmitting the avatar to a destination device. The disclosure includes capturing a second image of the face of the person on a source device. The disclosure includes calculating expression information based on the second image of the face of the person, with the expression information approximating an expression on the face of the person as captured in the second image. The disclosure includes transmitting the expression information from the source device to the destination device. The disclosure includes animating the avatar on a display component of the destination device using the expression information.

Abstract: Font recognition and similarity determination techniques and systems are described. In a first example, localization techniques are described to train a model using machine learning (e.g., a convolutional neural network) using training images. The model is then used to localize text in a subsequently received image, and may do so automatically and without user intervention, e.g., without specifying any of the edges of a bounding box. In a second example, a deep neural network is directly learned as an embedding function of a model that is usable to determine font similarity. In a third example, techniques are described that leverage attributes described in metadata associated with fonts as part of font recognition and similarity determinations.

Abstract: A system for object and information collection comprises a handheld tool to grab the object. The handheld tool comprises a pole with a handle, a trigger, a grabber mechanism at an opposite end, and a logic system attached to the pole, wherein once a user actuates the trigger to pick up an object with the grabber mechanism, the logic system transmits a capture signal to initiate a classification event. A classification application executing on a processor is responsive to receiving the capture signal from the logic system to capture information associated with the object and assign an object classification to the object based at least in part the captured information. At least one of a portion of the information and the assigned object classification is transmitted over network to an analytics cloud service to perform data aggregation and analysis.

Abstract: Disclosed are an image calibration method and an image calibration apparatus. The image calibration method is adapted to the image calibration apparatus. The image calibration method includes: step (A): capturing an input image having a calibration pattern, wherein the calibration pattern includes at least one frame and an analysis block, the analysis block is surrounded by the frame, and the analysis block includes a plurality of characteristic patterns separated from each other; step (B): determining whether at least one frame is within the input image; step (C): capturing the analysis block when the at least one frame is within the input image; and step (D): executing one of a displacement calibration, a scaling ratio, a rotation calibration, a keystone calibration or a combination thereof for the input image according to positions of the characteristic patterns within the analysis block to generate an output image.

Abstract: Devices, methods, and computer-readable media are disclosed describing an adaptive approach for image bracket selection and fusion, e.g., to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV? images, EV+ images, long exposure (or synthetic long exposure) images, EV0/EV? image pairs, etc., which are received according to a particular pattern. When a capture request is received, a set of rules and/or a decision tree may be used to evaluate one or more capture conditions associated with the images from the incoming image stream and determine which two or more images to select for a fusion operation. A noise reduction process may optionally be performed on the selected images before (or after) the registration and fusion operations.

Abstract: A processing system comprises a processor and a memory having computer readable instructions stored thereon. The computer readable instructions, when executed by the processor, cause the system to obtain a reference tree of nodes and linkages based on a reference three dimensional volumetric representation of a branched anatomical formation in a reference state. The computer readable instructions also cause the system to obtain a reference three dimensional geometric model based on the reference tree and detect deformation of the branched anatomical formation due to anatomical motion based on measurements from a shape sensor. The computer readable instructions also cause the system to obtain a deformed tree of nodes and linkages based on the detected deformation and create a three dimensional deformation field that represents the detected deformation of the branched anatomical formation.

Abstract: An electronic apparatus and method for adaptive sub-band based coding of hierarchical transform coefficients of a 3D point cloud, is provided. The electronic apparatus stores the 3D point cloud and generates a plurality of voxels from the 3D point cloud. The electronic apparatus generates a plurality of hierarchical transform coefficients by application of a hierarchical transform scheme on the generated plurality of voxels and classifies the plurality of hierarchical transform coefficients into a plurality of sub-bands of hierarchical transform coefficients. The plurality of hierarchical transform coefficients are classified based on a weight of each of the plurality of hierarchical transform coefficients.

Abstract: Method and system for dynamically modifying visual rendering of a visual element in a computer generated environment from an interactive computer simulation. Pre-identified distinctive visual characteristics are associated with the visual element. A tangible instrument module is sued to provide one or more commands for controlling a simulated vehicle of the interactive computer simulation. At the interactive computer simulation station, dynamically modifying the one or more pre-identified distinctive visual characteristics of the visual element is performed considering at least a relative directional vector between the simulated vehicle and the visual element in the computer generated environment, the relative directional vector being determined in real-time during execution of the interactive computer simulation prior to rendering the visual element for display.

Abstract: Techniques for performing a prediction task using a multi-modal statistical model configured to receive input data from multiple modalities including input data from a first modality and input data from a second modality different from the first modality.

Abstract: The present invention relates to an inspection system and more particularly to a system and method for inspection of wet ophthalmic lens, preferably in an automated lens manufacturing line. The inspection system provides for capturing multiple images of an ophthalmic lens using multiple cameras, each with a customized optical unit which may use wavelength filters, and the ophthalmic lens illuminated by multiple lighting modules each configured for a different wavelength, or a different polarization and triggered to strobe the illumination at the same instance or at different instances in the time domain. Suitable filters used in the optical module for each camera ensures appropriate images at different illuminating wavelength, especially when all the illuminations are strobed at the same time. Images captured and inspected by this configuration aids in improvement in method of inspection with enhanced degree of reliability and quality.

Abstract: Fluid properties like viscosity, yield strength, and density may be measured by analyzing fluid motion in response to disturbing the surface of the fluid. For example, a method may include disturbing a surface of a fluid in one or more locations, thereby forming a deformation and waves at the surface of the fluid for the one or more locations; imaging and measuring at least one selected from the group consisting of the deformation, the waves, and a combination thereof; and calculating a property of the fluid based on the at least one selected from the group consisting of the deformation, the waves, and a combination thereof, the property selected from the group consisting of viscosity, yield strength, density, and any combination thereof.

Abstract: A method performed by a mobile terminal may include receiving an image that includes text, translating the text into another language and superimposing and displaying the translated text over the received image.

Abstract: Disclosed are an image color enhancement method and a device. The method comprises: obtaining a first saturation of any pixel point in an image; processing the first saturation according to a first saturation conversion function to obtain a slope corresponding to the first saturation; obtaining a second saturation conversion function according to local detail information if the slope is smaller than a first preset threshold; processing the first saturation according to the second saturation conversion function to obtain a second saturation of the pixel point; calculating a target brightness value according to the second saturation; and adjusting an original brightness value to the target brightness value. Thereby, a different saturation enhancement method is adopted for the pixel points which are easy to cause the details in the image lost, so that the image vividness is enhanced, and the detail information is preserved to improve the sharpness.

Abstract: Embodiments discussed herein relate to accessing a digitized image associated with a patient of tissue demonstrating breast cancer pathology; segmenting a tumor region represented in the digitized image; segmenting collagen fibers represented in the tumor region; computing collagen vectors based on the segmented collagen fibers; generating an orientation co-occurrence matrix based on the collagen vectors; computing a collagen fiber orientation disorder feature based on the co-occurrence matrix; upon determining that the collagen fiber orientation feature exceeds a threshold value: generating a prognosis of the region of tissue as unlikely to experience breast cancer recurrence; upon determining that the collagen fiber orientation feature is less than or equal to the threshold value: generating a prognosis of the region of tissue as likely to experience breast cancer recurrence; classifying the patient as high-risk of recurrence or low-risk of recurrence based, at least in part, on the prognosis; and displayin

Abstract: A neural network model receives color data for a sequence of images corresponding to a dynamic scene in three-dimensional (3D) space. Motion of objects in the image sequence results from a combination of a dynamic camera orientation and motion or a change in the shape of an object in the 3D space. The neural network model generates two components that are used to produce a 3D motion field representing the dynamic (non-rigid) part of the scene. The two components are information identifying dynamic and static portions of each image and the camera orientation. The dynamic portions of each image contain motion in the 3D space that is independent of the camera orientation. In other words, the motion in the 3D space (estimated 3D scene flow data) is separated from the motion of the camera.

Abstract: Methods and systems for remotely detecting gases and emissions of gases are provided. Data is collected from a scene using a sensor system. The data is initially optionally processed as 1D data to remove noise, and is then assigned a confidence value by processing the 1D data using a neural network. The confidence value is related to a likelihood that an emission has been detected at a particular location. The processed 1D data, including the confidence value, is gridded into 2D space. The 2D data is then processed using a neural network to assign a 2D confidence value. The 2D data can be fused with RGB data to produce a map of emission source locations. The data identifying emissions can also be processed using a neural network to determine and output emission rate data.

Abstract: A face recognition method applied to establish authentic or artificial faces before searching for a person match in a database includes establishing a deep network model, obtaining training data and training the deep network model using the training data. An original image of a human face and a depth image corresponding to the original image are obtained, and authenticity or artificiality is determined by preset methods including use of cosine similarity algorithm. Matching an original image determined as authentic against face images pre-stored in an image database and outputting any match, when the original image is the image of a real person. A face recognition device is also provided.

Abstract: In embodiments, obtaining a plurality of image sets associated with a geographical region and a time period, wherein each image set of the plurality of image sets comprises multi-spectral and time series images that depict a respective particular portion of the geographical region during the time period, and predicting one or more crop types growing in each of particular locations within the particular portion of the geographical region associated with an image set of the plurality of image sets. Determining a crop type classification for each of the particular locations based on the predicted one or more crop types for the respective particular locations, and generating a crop indicative image comprising at least one image of the multi-spectral and time series images of the image set overlaid with indications of the crop type classification determined for the respective particular locations.

Abstract: An information-processing apparatus includes: an image acquisition unit configured to acquire information on a predetermined item as image information from an image file; a comparison unit configured to compare the image information with text data relating to the image file; and a notification unit configured to perform a notification in a case where a result of the comparison indicates a mismatch between the image information and the text data.

Abstract: Systems and methods monitor a workspace for safety purposes using sensors distributed about the workspace. The sensors are registered with respect to each other, and this registration is monitored over time. Occluded space as well as occupied space is identified, and this mapping is frequently updated.