Abstract: A seat for an off-road racing vehicle including a single piece molded shell having a seat back with a head rest, side panels and a seat bottom with a thigh support, where the shell is covered by an upholstery. The seat also includes a seat cushion positioned on the seat bottom and having two foam layers, namely, a top thin foam layer and a bottom thick energy absorbing foam layer that are secured together, where the combination of the layers is capable of absorbing high energy Z-direction forces. In one non-limiting embodiment, the top layer is a methylenediphenyl isocyanate (MDI) polyurethane foam and is 12 mm thick, and the bottom layer is an open-cell energy absorbing urethane foam and is 38 mm thick.

Abstract: A seat for an off-road racing vehicle including a single piece molded shell having a seat back with a head rest, side panels and a seat bottom with a thigh support, where the shell is covered by an upholstery. The seat also includes a seat cushion positioned on the seat bottom and having two foam layers, namely, a top thin foam layer and a bottom thick energy absorbing foam layer that are secured together, where the combination of the layers is capable of absorbing high energy Z-direction forces. In one non-limiting embodiment, the top layer is a methylenediphenyl isocyanate (MDI) polyurethane foam and is 12 mm thick, and the bottom layer is an open-cell energy absorbing urethane foam and is 38 mm thick.

Abstract: A seat cushion for a seat in a high performance off-road racing vehicle. The seat cushion includes two foam layers, namely, a top thin foam layer and a bottom thick energy absorbing foam layer that are secured together, where the combination of the layers are capable of absorbing high energy Z-direction forces. In one non-limiting embodiment, the top layer is a methylenediphenyl isocyanate (MDI) polyurethane foam and is 12 mm thick, and the bottom layer is an open-cell energy absorbing urethane foam and is 38 mm thick.

Abstract: A method includes receiving a first image including color data and depth data, determining a viewpoint associated with an augmented reality (AR) and/or virtual reality (VR) display displaying a second image, receiving at least one calibration image including an object in the first image, the object being in a different pose as compared to a pose of the object in the first image, and generating the second image based on the first image, the viewpoint and the at least one calibration image.

Abstract: A seat cushion for a seat in a high performance off-road racing vehicle. The seat cushion includes two foam layers, namely, a top thin foam layer and a bottom thick energy absorbing foam layer that are secured together, where the combination of the layers are capable of absorbing high energy Z-direction forces. In one non-limiting embodiment, the top layer is a methylenediphenyl isocyanate (MDI) polyurethane foam and is 12 mm thick, and the bottom layer is an open-cell energy absorbing urethane foam and is 38 mm thick.

Abstract: According to an aspect, a method for neural rerendering includes obtaining a three-dimensional (3D) model representing a scene of a physical space, where the 3D model is constructed from a collection of input images, rendering an image data buffer from the 3D model according to a viewpoint, where the image data buffer represents a reconstructed image from the 3D model, receiving, by a neural rerendering network, the image data buffer, receiving, by the neural rerendering network, an appearance code representing an appearance condition, and transforming, by the neural rerendering network, the image data buffer into a rerendered image with the viewpoint of the image data buffer and the appearance condition specified by the appearance code.

Abstract: Techniques of estimating lighting from portraits includes generating a lighting estimate from a single image of a face based on a machine learning (ML) system using multiple bidirectional reflection distribution functions (BRDFs) as a loss function. In some implementations, the ML system is trained using images of faces formed with HDR illumination computed from LDR imagery. The technical solution includes training a lighting estimation model in a supervised manner using a dataset of portraits and their corresponding ground truth illumination.

Abstract: Three-dimensional (3D) performance capture and machine learning can be used to re-render high quality novel viewpoints of a captured scene. A textured 3D reconstruction is first rendered to a novel viewpoint. Due to imperfections in geometry and low-resolution texture, the 2D rendered image contains artifacts and is low quality. Accordingly, a deep learning technique is disclosed that takes these images as input and generates more visually enhanced re-rendering. The system is specifically designed for VR and AR headsets, and accounts for consistency between two stereo views.

Abstract: A method, computer program product, and a system where a processor(s) monitors communications between one or more clients to a query engine, to identify requests to execute queries on the database resource. Based on identifying a requested query, the processor(s) applies cognitive analysis algorithms to parse components of the requested query, to identify components in the requested query that indicate an execution success measure for the requested query. The processor(s) determines the execution success measure for the requested query and assigns an execution action to the requested query: pre-empting the requested query or executing the requested query. The processor(s) facilitates this action on the requested query.

Abstract: A method includes receiving a first image including color data and depth data, determining a viewpoint associated with an augmented reality (AR) and/or virtual reality (VR) display displaying a second image, receiving at least one calibration image including an object in the first image, the object being in a different pose as compared to a pose of the object in the first image, and generating the second image based on the first image, the viewpoint and the at least one calibration image.

Abstract: According to an aspect, a method for neural rerendering includes obtaining a three-dimensional (3D) model representing a scene of a physical space, where the 3D model is constructed from a collection of input images, rendering an image data buffer from the 3D model according to a viewpoint, where the image data buffer represents a reconstructed image from the 3D model, receiving, by a neural rerendering network, the image data buffer, receiving, by the neural rerendering network, an appearance code representing an appearance condition, and transforming, by the neural rerendering network, the image data buffer into a rerendered image with the viewpoint of the image data buffer and the appearance condition specified by the appearance code.

Abstract: In at least one aspect, a method can include generating a respective set of training set of images for each label in a handedness model by: receiving the label at an image capturing device, obtaining a set of captured images by recording a pass-through image of a user placing a target object within an overlay of a bounding area animation, the target object corresponding with the label, and associating the label with each image in the set of captured images. The method includes training, using the training images, the handedness model to provide a correct label for an input image.

Abstract: Embodiments of present disclosure discloses system and method for acquisition of optimal images of object in multi-layer sample. Initially, images for FOV of multi-layer sample comprising objects are retrieved. Each of images are captured by varying focal depth of image capturing unit associated with system. Further, objects associated with multi-layer sample in FOV are identified. For identification, cumulative foreground mask of FOV is obtained based on adaptive thresholding performed on foreground image of FOV. Based on contour detection performed on cumulative foreground mask of FOV, object masks, corresponding to objects, is obtained for identifying objects. Further, sharpness of each of images associated with each of object masks is computed. Based on sharpness, optimal images from images for each of objects is selected for acquisition of optimal images of objects in multi-layer sample.

Abstract: A method, computer program product, and a system where a processor(s) monitors communications between one or more clients to a query engine, to identify requests to execute queries on the database resource. Based on identifying a requested query, the processor(s) applies cognitive analysis algorithms to parse components of the requested query, to identify components in the requested query that indicate an execution success measure for the requested query. The processor(s) determines the execution success measure for the requested query and assigns an execution action to the requested query: pre-empting the requested query or executing the requested query. The processor(s) facilitates this action on the requested query.

Abstract: Methods, systems, and computer program products are described herein for minimizing the downtime for nodes in a network-accessible server set. The downtime may be minimized by determining an optimal timeout value for which a fabric controller waits to perform a recovery action. The optimal timeout value may be determined for each cluster in the network-accessible server set. The optimal timeout value advantageously reduces the overall downtime for customer workloads running on a node for which contact has been lost. The optimal timeout value for each cluster may be based on a predictive model based on the observed historical patterns of the nodes within that cluster. In the event that an optimal timeout value is not determined for a particular cluster (e.g., due to a lack of observed historical patterns), the fabric controller may fall back to a less than optimal timeout value.

Abstract: A configured machine performs image matching and retrieval of natural images that may depict logos. The machine generates and uses color-localized spatial masks, which may be computationally less expensive than spatial verification techniques. Key points are detected within images that form a reference database of images. Local masks are defined by the machine around each key point based on the scale and orientation of the key point. To utilize color information presented in logo images, ordered color histograms may be extracted by the machine from locally masked regions of each image. A cascaded index may then be constructed for both visual descriptors and color histograms. For faster matching, the cascaded index maps the visual descriptors and color histograms to a list of relevant or similar images. This list may then be ranked to generate relevant matches for an input query image.

Abstract: In at least one aspect, a method can include generating a respective set of training set of images for each label in a handedness model by: receiving the label at an image capturing device, obtaining a set of captured images by recording a pass-through image of a user placing a target object within an overlay of a bounding area animation, the target object corresponding with the label, and associating the label with each image in the set of captured images. The method includes training, using the training images, the handedness model to provide a correct label for an input image.

Abstract: Methods, systems, and computer program products are described herein for minimizing the downtime for nodes in a network-accessible server set. The downtime may be minimized by determining an optimal timeout value for which a fabric controller waits to perform a recovery action. The optimal timeout value may be determined for each cluster in the network-accessible server set. The optimal timeout value advantageously reduces the overall downtime for customer workloads running on a node for which contact has been lost. The optimal timeout value for each cluster may be based on a predictive model based on the observed historical patterns of the nodes within that cluster. In the event that an optimal timeout value is not determined for a particular cluster (e.g., due to a lack of observed historical patterns), the fabric controller may fall back to a less than optimal timeout value.

Abstract: A method for performing the following operations (not necessarily in the following order): (i) receiving by an augmented reality system, a series of images corresponding to views of the real world; (ii) processing, by the augmented reality system, the series of images to determine presence of a first object; (iii) determining, by the augmented reality system, that the first object meets a first set of conditions such that the first object belongs to a first object category; and (iv) responsive to the determination that the first object belongs to the first object category, providing an audio response in the form of one at least one of the following types of audio responses: communicating a predefined sound to an augmented reality user and/or changing audio characteristic(s) of a sound not generated by the augmented reality system which is being experienced by the augmented reality user.

Abstract: A method for performing the following operations (not necessarily in the following order): (i) receiving by an augmented reality system, a series of images corresponding to views of the real world; (ii) processing, by the augmented reality system, the series of images to determine presence of a first object; (iii) determining, by the augmented reality system, that the first object meets a first set of conditions such that the first object belongs to a first object category; and (iv) responsive to the determination that the first object belongs to the first object category, providing an audio response in the form of one at least one of the following types of audio responses: communicating a predefined sound to an augmented reality user and/or changing audio characteristic(s) of a sound not generated by the augmented reality system which is being experienced by the augmented reality user.