Abstract: Various embodiments enable a computing device to perform tasks such as processing an image to recognize text or an object in an image to identify a particular product or related products associated with the text or object. In response to recognizing the text or the object as being associated with a product available for purchase from an electronic marketplace, one or more advertisements or product listings associated with the product can be displayed to the user. Accordingly, additional information for the associated product can be displayed, enabling the user to learn more about and purchase the product from the electronic marketplace through the portable computing device.

Abstract: Techniques are described for providing functionality to allow a viewer of a television show to watch a “previously on” segment of an episode of the television show and be able to watch the scenes from prior episodes referenced in the “previously on” segment.

Abstract: Various embodiments provide methods and systems for providing a recommended volume level in presentation of media content. In some embodiments, volume adjustment events made by a user and/or similar users while watching media content can be detected and automatically recorded. The media content may include a plurality of segments. A normalized volume level for at least one segment of the media content can be determined by aggregating the recorded volume adjustment events corresponding to the at least one segment of the media content. When the media content is played back on a user device, at least some embodiments cause the at least one segment of the media content to be played back at a recommended volume level determined based at least in part upon one of the normalized audio level of the corresponding segment, the audio system of the user device, or historical data and personal profile of the user.

Abstract: A diverter assembly includes a tubing segment and one or more sleeve members disposed therein. The tubing segment includes apertures that are selectively alignable with apertures of an inner sleeve disposed within the tubing segment. The tubing segment includes a series of stops (e.g., shear pins) to arrest movement of the first sleeve within the bore of the tubing segment. A first one or more ball seats are included in the first sleeve such that deployment of a first ball and pressurization of the well above the first ball causes a first set of shear pins to fail, thereby allowing the first sleeve to slide downhole to cause apertures of the sleeve to align with apertures of the tubing segment, thereby causing fluid to flow to an annulus between the tubing segment and wellbore wall.

Abstract: An image creation and editing tool can use the data produced from training a neural network to add stylized representations of an object to an image. An object classification will correspond to an object representation, and pixel values for the object representation can be added to, or blended with, the pixel values of an image in order to add a visualization of a type of object to the image. Such an approach can be used to add stylized representations of objects to existing images or create new images based on those representations. The visualizations can be used to create patterns and textures as well, as may be used to paint or fill various regions of an image. Such patterns can enable regions to be filled where image data has been deleted, such as to remove an undesired object, in a way that appears natural for the contents of the image.

Abstract: A downhole tool subassembly has an outer sleeve with a first set of apertures extending from an inner bore of the outer sleeve. An intermediate sleeve positioned is within the outer sleeve and defines an intermediate flow path extending from an inner bore of the intermediate sleeve to a cavity formed between the uphole portion of the outer sleeve and the downhole portion of the intermediate sleeve. An inner sleeve is positioned within the intermediate sleeve and has an external sealing portion that restricts flow across the intermediate flow path when the downhole tool is in a first configuration.

Abstract: An image creation and editing tool can use the data produced from training a neural network to add stylized representations of an object to an image. An object classification will correspond to an object representation, and pixel values for the object representation can be added to, or blended with, the pixel values of an image in order to add a visualization of a type of object to the image. Such an approach can be used to add stylized representations of objects to existing images or create new images based on those representations. The visualizations can be used to create patterns and textures as well, as may be used to paint or fill various regions of an image. Such patterns can enable regions to be filled where image data has been deleted, such as to remove an undesired object, in a way that appears natural for the contents of the image.

Abstract: Systems and approaches are provided for optimizing self-portraiture. The background of the self-portrait can be enhanced by image registration or stitching techniques of images captured using one or more conventional cameras. Multiple standard resolution images can be stitched together to generate a panoramic or a composite image of a higher resolution. Foreground elements, such as one or more representations of users, can also be enhanced in various ways. The representations of the users can be composited to exclude undesirable elements, such as image data of one of the users extending her arm to capture the self-portrait. An ideal pose of the users can automatically be selected and other image enhancements, such as histogram optimization, brightness and contrast optimization, color-cast correction, or reduction or removal of noise, can automatically be performed to minimize user effort in capturing self-portraits.

Abstract: A downhole tool subassembly having an outer sleeve with a first set of apertures extending from an inner bore through an external surface of the outer sleeve. The downhole tool subassembly further includes a pin coupled to the outer sleeve and extending inward from the inner bore of the outer sleeve, and an inner sleeve slidingly engaged with the with outer sleeve. The inner sleeve has a slot and a second set of apertures extending from a sleeve bore of the inner sleeve through an external surface of the inner sleeve, and is operable to restrict flow across the first set of apertures when the inner sleeve is in a first position. The pin engages the slot, which includes a first tracking path and a second tracking path.

Abstract: A set of training images is obtained by analyzing text associated with various images to identify images likely demonstrating a visual attribute. Localization can be used to extract patches corresponding to these attributes, which can then have features or feature vectors determined to train, for example, a convolutional neural network. A query image can be received and analyzed using the trained network to determine a set of items whose images demonstrate visual similarity to the query image at least with respect to the attribute of interest. The similarity can be output from the network or determined using distances in attribute space. Content for at least a determined number of highest ranked, or most similar, items can then be provided in response to the query image.

Abstract: Various embodiments enable the identification of semi-structured text entities in an imager. The identification of the text entities is a relatively simple problem when the text is stored in a computer and free of errors, but much more challenging if the source is the output of an optical character recognition (OCR) engine from a natural scene image. Accordingly, output from an OCR engine is analyzed to isolate a character string indicative of a text entity. Each character of the string is then assigned to a character class to produce a character class string and the text entity of the string is identified based in part on a pattern of the character class string.

Abstract: Various embodiments identify differences between frame sequences of a video. For example, to determine a difference between two versions of a video, a fingerprint of each frame of the two versions is generated. From the fingerprints, a run-length encoded representation of each version is generated. The fingerprints which appear only once (i.e., unique fingerprints) in the entire video are identified from each version and compared to identify matching unique fingerprints across versions. The matching unique fingerprints are sorted and filtered to determine split points, which are used to align the two versions of the video. Accordingly, each version is segmented into smaller frame sequences using the split points. Once segmented, the individual frames of each segment are aligned across versions using a dynamic programming algorithm. After aligning the segments at a frame level, the segments are reassembled to generate a global alignment output.

Abstract: Approaches are described for enabling a user to create an accurate perspective rendering of a source (e.g., a scene, object, subject, point of interest, etc.) on a drawing surface. For example, various approaches enable superimposition of the source being viewed upon a drawing surface upon which a user is drawing. In this way, the user can view both the source and drawing surface simultaneously. This allows the user to duplicate key points of the source on the drawing surface by viewing a display of a device, thus aiding in the accurate rendering of perspective.

Abstract: Various embodiments enable a process to automatically attempt to select the most relevant words associated with products available for purchase from an electronic marketplace from an image frame. For example, an image frame containing text can be obtained and analyzed with an optical character recognition. The recognized words can then be preprocessed using various filtering and scoring techniques to narrow down a volume of text to a few relevant query terms. These query terms can then be sent to a search engine associated with the electronic marketplace to return relevant products to a user.

Abstract: A video segmentation system can be utilized to automate segmentation of digital video content. Features corresponding to visual, audio, and/or textual content of the video can be extracted from frames of the video. The extracted features of adjacent frames are compared according to a similarity measure to determine boundaries of a first set of shots or video segments distinguished by abrupt transitions. The first set of shots is analyzed according to certain heuristics to recognize a second set of shots distinguished by gradual transitions. Key frames can be extracted from the first and second set of shots, and the key frames can be used by the video segmentation system to group the first and second set of shots by scene. Additional processing can be performed to associate metadata, such as names of actors or titles of songs, with the detected scenes.

Abstract: Image processing techniques for self-captured images are disclosed. An image can be captured during activation of an illumination element of a mobile device. Presence of a representation of the mobile device can be determined in the captured image based at least in part upon locating a reflection of an illumination produced by the illumination element. Dimensions of the representation of the mobile device can be determined and compared to actual dimensions of the mobile device to provide a scaling factor. The scaling factor can be used to determine the size of various objects, including articles of clothing, in the image.

Abstract: Approaches include using a machine learning-based approach to generating search strings and refinements based on a specific item represented in an image. For example, a classifier that is trained on descriptions of images can be provided. An image that includes a representation of an item of interest is obtained. The image is analyzed using the classifier algorithm to determine a first term representing a visual characteristic of the image. Then, the image is analyzed again to determine a second term representing another visual characteristic of the image based at least in part on the first term. Additional terms can be determined to generate a description of the image, including characteristics of the item of interest. Based on the determined characteristics of the item of interest, a search query and one or more refinements can be generated.

Abstract: Various embodiments enable a computing device to perform tasks such as highlighting words in an augmented reality view that are important to a user. For example, word lists can be generated and the user, by pointing a camera of a computing device at a volume of text, can cause words from the word list within the volume of text to be highlighted in a live field of view of the camera displayed thereon. Accordingly, users can quickly identify textual information that is meaningful to them in an Augmented Reality view to aid the user in sifting through real-world text.

Abstract: Techniques are described for providing functionality to allow a viewer of a television show to watch a “previously on” segment of an episode of the television show and be able to watch the scenes from prior episodes referenced in the “previously on” segment.

Abstract: A video segmentation system can be utilized to automate segmentation of digital video content. Features corresponding to visual, audio, and/or textual content of the video can be extracted from frames of the video. The extracted features of adjacent frames are compared according to a similarity measure to determine boundaries of a first set of shots or video segments distinguished by abrupt transitions. The first set of shots is analyzed according to certain heuristics to recognize a second set of shots distinguished by gradual transitions. Key frames can be extracted from the first and second set of shots, and the key frames can be used by the video segmentation system to group the first and second set of shots by scene. Additional processing can be performed to associate metadata, such as names of actors or titles of songs, with the detected scenes.