Abstract: Embodiments of the present disclosure generally relate to methods for forming a waveguide. Methods may include measuring a waveguide substrate, the waveguide having a substrate thickness distribution; and depositing an index-matched layer onto a surface of the waveguide, the index-matched layer having a first surface disposed on the waveguide substrate and a second surface opposing the first surface, wherein the index-matched layer is disposed only over a portion of the waveguide substrate, and a device slope of a second surface of the index-matched layer is substantially the same as the waveguide slope of the first surface of the waveguide.

Abstract: Example embodiments relate to a network-based workflow system, employed for receiving workflows, defining one or more data-object types based on the workflows, generating data-objects, assigning a workflow from among the one or more workflows to the data-object, and managing the data-object through various states of based on the workflow. As discussed, a “workflow” refers to orchestrated and repeatable patterns enabled by a systematic organization of resources into processes that transform and modify presentations of data-objects based on corresponding data-object states. A workflow may therefore comprise a set of states, wherein each state is linked to another state by one or more transitions, and wherein the transitions are associated with a set of events which may occur at each state.

Abstract: Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Abstract: Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Abstract: Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Abstract: Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Abstract: Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Abstract: Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Abstract: Signature-based program identification apparatus and methods for use with digital audio and/or video systems are disclosed. The disclosed systems and methods develop signatures of digital audio and/or video content from a digital data stream at two or more sites and compare the signatures to one another to identify the content.

Abstract: Digital video signature apparatus and methods for use with video program identification systems are disclosed. The example apparatus and methods generate a signature associated with a video program. An example system includes a frame scanner to scan video frames associated with the video program. The frame scanner is to select a video frame based on a number of intra-coded macro blocks within the video frame. The example system also includes an intra-coded macro block extractor to extract intra-coded macro blocks from the video frame and a scaled image extractor to extract a scaled image from the intra-coded macro blocks. A signature generator is also included in the example system to calculate a plurality of centroids associated with video frame based on the scaled image and to form the signature based on the plurality of centroids.

Abstract: Digital video signature apparatus and methods for use with video program identification systems are disclosed. The example apparatus and methods generate a signature associated with a video program. An example system includes a frame scanner to scan video frames associated with the video program. The frame scanner is to select a video frame based on a number of intra-coded macro blocks within the video frame. The example system also includes an intra-coded macro block extractor to extract intra-coded macro blocks from the video frame and a scaled image extractor to extract a scaled image from the intra-coded macro blocks. A signature generator is also included in the example system to calculate a plurality of centroids associated with video frame based on the scaled image and to form the signature based on the plurality of centroids.

Abstract: Digital video signature apparatus and methods for use with video program identification systems are disclosed. The example apparatus and methods generate a signature associated with a video program. An example system includes a frame scanner to scan video frames associated with the video program. The frame scanner is to select a video frame based on a number of intra-coded macro blocks within the video frame. The example system also includes an intra-coded macro block extractor to extract intra-coded macro blocks from the video frame and a scaled image extractor to extract a scaled image from the intra-coded macro blocks. A signature generator is also included in the example system to calculate a plurality of centroids associated with video frame based on the scaled image and to form the signature based on the plurality of centroids.

Abstract: Buildings are described that incorporate at least a folding building module and a complementary building module that also can be a folding building module. The building modules can be shipped to the building site separately and can be unfolded and connected quickly. The described foldable houses and buildings exhibit more design flexibility, are formed from easily transported building modules, and/or allow folded building modules that are substantially in finished condition. Additionally, methods for forming the buildings and houses are described.

Abstract: Methods and apparatus to methods and apparatus to identify images in print advertisements are disclosed. An example method comprises computing a first image feature vector for a first presented image, comparing the first image feature vector to a second image feature vector, and when the first image feature vector matches the second image feature vector, storing printed-media information associated with the first presented image in a database record associated with the second image feature vector.

Abstract: Signature-based program identification apparatus and methods for use with digital audio and/or video systems are disclosed. The disclosed systems and methods develop signatures of digital audio and/or video content from a digital data stream at two or more sites and compare the signatures to one another to identify the content.

Abstract: Signature-based program identification apparatus and methods for use with digital audio and/or video systems are disclosed. The disclosed systems and methods develop signatures of digital audio and/or video content from a digital data stream at two or more sites and compare the signatures to one another to identify the content.