Abstract: An apparatus configured to be head-worn by a user, includes: a screen configured to present graphics for the user; a camera system configured to view an environment in which the user is located; and a processing unit coupled to the camera system, the processing unit configured to: obtain locations of features for an image of the environment, wherein the locations of the features are identified by a neural network; determine a region of interest for one of the features in the image, the region of interest having a size that is less than a size of the image; and perform a corner detection using a corner detection algorithm to identify a corner in the region of interest.

Abstract: An apparatus configured to be head-worn by a user, includes: a screen configured to present graphics for the user; a camera system configured to view an environment in which the user is located; and a processing unit coupled to the camera system, the processing unit configured to: obtain locations of features for an image of the environment, wherein the locations of the features are identified by a neural network; determine a region of interest for one of the features in the image, the region of interest having a size that is less than a size of the image; and perform a corner detection using a corner detection algorithm to identify a corner in the region of interest.

Abstract: Systems and methods for predicting head pose for a rendering engine of an augmented or virtual reality device can include a recurrent neural network (RNN) that accepts a time series of head pose data and outputs a predicted head pose. The recurrent neural network can include one or more long short term memory (LSTM) units or gated recurrent units (GRUs). A fully connected (FC) layer can accept input from the RNN and output a 3 degree-of-freedom (DOF) head pose (e.g., angular orientation or spatial position) or a 6 DOF head pose (e.g., both angular orientation and spatial position). The rendering engine can use the predicted head pose to generate and display virtual content to the user at the time the user looks toward the position of the virtual content, which reduces system latency and improves user experience.

Abstract: Systems and methods for predicting head pose for a rendering engine of an augmented or virtual reality device can include a recurrent neural network (RNN) that accepts a time series of head pose data and outputs a predicted head pose. The recurrent neural network can include one or more long short term memory (LSTM) units or gated recurrent units (GRUs). A fully connected (FC) layer can accept input from the RNN and output a 3 degree-of-freedom (DOF) head pose (e.g., angular orientation or spatial position) or a 6 DOF head pose (e.g., both angular orientation and spatial position). The rendering engine can use the predicted head pose to generate and display virtual content to the user at the time the user looks toward the position of the virtual content, which reduces system latency and improves user experience.

Abstract: A method and system for determining a position of an object with respect to a semi-transparent container, by: receiving, from a camera attached to a semi-transparent container, an image of a scene in proximity to the semi-transparent container; detecting, by an object detector, a new object present in the image, else marking the image as being an image indicative of a current state of the semi-transparent container; cropping, by a computer processor, the image to produce a cropped object image; analyzing, by the computer processor, the cropped object image; and assigning, by the computer processor, a confidence score in a numeric range to the cropped object image, wherein a score at one end of the range indicates the new object corresponding to the cropped object image is inside the semi-transparent container, and wherein a score at the other end of the range indicates the new object is outside.

Abstract: Systems and methods for predicting head pose for a rendering engine of an augmented or virtual reality device can include a recurrent neural network (RNN) that accepts a time series of head pose data and outputs a predicted head pose. The recurrent neural network can include one or more long short term memory (LSTM) units or gated recurrent units (GRUs). A fully connected (FC) layer can accept input from the RNN and output a 3 degree-of-freedom (DOF) head pose (e.g., angular orientation or spatial position) or a 6 DOF head pose (e.g., both angular orientation and spatial position). The rendering engine can use the predicted head pose to generate and display virtual content to the user at the time the user looks toward the position of the virtual content, which reduces system latency and improves user experience.

Abstract: Systems and methods for predicting head pose for a rendering engine of an augmented or virtual reality device can include a recurrent neural network (RNN) that accepts a time series of head pose data and outputs a predicted head pose. The recurrent neural network can include one or more long short term memory (LSTM) units or gated recurrent units (GRUs). A fully connected (FC) layer can accept input from the RNN and output a 3 degree-of-freedom (DOF) head pose (e.g., angular orientation or spatial position) or a 6 DOF head pose (e.g., both angular orientation and spatial position). The rendering engine can use the predicted head pose to generate and display virtual content to the user at the time the user looks toward the position of the virtual content, which reduces system latency and improves user experience.

Abstract: A joint tape to be applied to wallboard is provided and includes a base substrate having opposing sides. In certain embodiments, a first adhesive layer is applied to one of the sides of the base substrate and a second adhesive layer is applied to the first adhesive layer, where the first adhesive layer is different than the second adhesive layer. In certain other embodiments, two different adhesives are used in a single adhesive layer. In use, the joint tape is positioned over and removably secured to a joint or corner between adjacent wallboard panels using the first adhesive layer. After the joint tape is in position, joint compound is applied to the joint tape, and the water in the joint tape activates it to form a secure bond with the wallboard panels.

Abstract: A gap finishing tape for use with drywall applications includes a trim strip body extending along a central body axis, a hot melt adhesive extending along the central body axis, and a backing paper. The trim strip body includes a first surface, a second surface opposite the first surface, a first side, and a second side opposite the first side, and is at least partially constructed from a metallic material. The backing paper is at least partially secured to the second surface of the trim strip body. The trim strip body is at least partially embedded in the hot melt adhesive.

Abstract: A non-swelling joint tape for use with drywall applications includes a tapered trim strip body extending along a central body axis and a non-swelling backing paper. The tapered trim strip body includes a first surface, a second surface opposite the first surface, a first side, and a second side opposite the first side, and is at least partially constructed from a first dimensionally stable material. The non-swelling backing paper is at least partially secured to the second surface of the tapered trim strip body and is at least partially constructed from a second dimensionally stable material. The tapered trim strip body is dimensioned such that a first thickness between the first surface and the second surface at the central body axis is greater than a second thickness between the first surface and the second surface at the first side and the second side.

Abstract: An apparatus configured to be head-worn by a user, includes: a screen configured to present graphics for the user; a camera system configured to view an environment in which the user is located; and a processing unit coupled to the camera system, the processing unit configured to: obtain locations of features for an image of the environment, wherein the locations of the features are identified by a neural network; determine a region of interest for one of the features in the image, the region of interest having a size that is less than a size of the image; and perform a corner detection using a corner detection algorithm to identify a corner in the region of interest.

Abstract: A joint tape for drywall includes a substrate layer having an elongate shape in a lengthwise direction and being flexible in the lengthwise direction and in a transverse direction. The tape further includes a covering layer disposed in bonding relation on the substrate layer. The covering layer is rigid in the transverse direction and configured to withstand compressive forces applied generally in the transverse direction and shear stresses applied generally along the transverse direction.

Abstract: A joint tape for drywall includes a substrate layer having an elongate shape in a lengthwise direction and being flexible in the lengthwise direction and in a transverse direction. The tape further includes a covering layer disposed in bonding relation on the substrate layer. The covering layer is rigid in the transverse direction and configured to withstand compressive forces applied generally in the transverse direction and shear stresses applied generally along the transverse direction.

Abstract: A non-swelling joint tape for use with drywall applications includes a tapered trim strip body extending along a central body axis and a non-swelling backing paper. The tapered trim strip body includes a first surface, a second surface opposite the first surface, a first side, and a second side opposite the first side, and is at least partially constructed from a first dimensionally stable material. The non-swelling backing paper is at least partially secured to the second surface of the tapered trim strip body and is at least partially constructed from a second dimensionally stable material. The tapered trim strip body is dimensioned such that a first thickness between the first surface and the second surface at the central body axis is greater than a second thickness between the first surface and the second surface at the first side and the second side.

Abstract: A gap finishing tape for use with drywall applications includes a trim strip body extending along a central body axis, a hot melt adhesive extending along the central body axis, and a backing paper. The trim strip body includes a first surface, a second surface opposite the first surface, a first side, and a second side opposite the first side, and is at least partially constructed from a metallic material. The backing paper is at least partially secured to the second surface of the trim strip body. The trim strip body is at least partially embedded in the hot melt adhesive.

Abstract: Disclosed herein are gypsum products with at least one high efficiency heat sink additive. The gypsum products, e.g., gypsum panels, are less susceptible to the damaging effects of extreme heat as the temperature rises due to the presence of the at least one additive.

Abstract: A joint tape for drywall includes a substrate layer having an elongate shape in a lengthwise direction and being flexible in the lengthwise direction and in a transverse direction. The tape further includes a covering layer disposed in bonding relation on the substrate layer. The covering layer is rigid in the transverse direction and configured to withstand compressive forces applied generally in the transverse direction and shear stresses applied generally along the transverse direction.

Abstract: A joint tape for drywall includes a substrate layer having an elongate shape in a lengthwise direction and being flexible in the lengthwise direction and in a transverse direction. The tape further includes a covering layer disposed in bonding relation on the substrate layer. The covering layer is rigid in the transverse direction and configured to withstand compressive forces applied generally in the transverse direction and shear stresses applied generally along the transverse direction.

Abstract: There is provided a system configured to receive a plurality of images, analyze a set of features of the plurality of images to determine a difference between a first training performance of a plurality of independent detectors based on one or more of individual attributes and a second training performance of a plurality of joint detectors based on one or more of composite attributes, select, based on the analyzing, either one of the plurality of independent detectors or one of the plurality of joint detectors for identifying a plurality of objects in the plurality of images, and identify the plurality of objects in the plurality of images, using the selected one of the plurality of independent detectors utilizing the one or more of the individual attributes or using the selected one of the plurality of joint detectors utilizing the one or more of the composite attributes.

Abstract: There is provided a system comprising a memory and a processor configured to receive a plurality of images, train a plurality of independent detectors for identifying a first plurality of objects in the plurality of images based on individual attributes including a first attribute and a second attribute, train a plurality of joint detectors for identifying the first plurality of objects in the plurality of images based on composite attributes including a plurality of composite attributes each including the first attribute and the second attribute, analyze features of the plurality of images to determine a difference between a first training performance of the independent detectors and a second training performance of the joint detectors, and select, based on the analyzing, between using the independent detectors and using the joint detectors for identifying a second plurality of objects in the plurality of images using a first new attribute and a second new attribute in the attribute database.