A9.com, Inc.

Google Inc.

William Brendel

David Creighton Mott

Nityananda Jayadevaprakash

Scott Paul Robertson

Arnab Sanat Kumar Dhua

Colin Jon Taylor

Kathy Wing Lam Ma

Adam Neustein

Sunil Ramesh

Mark Jay Nitzberg

Zur Nehushtan

Shruti Sheorey

Jie Feng

Jason Matthew Toff

Thomas Benton Bridgwater

John A Gregg

Mark Scott Waldo

Sean Niu

Pinkee Rasik Patel Gupta

Kaolin Imago Fire

Daniel Luke Schiffman

Christopher Joseph Hawley

Because not all companies register or obtain barcodes (or other encodings or identifiers) from a single, consistent source, and because different companies can be associated with the same barcode at different times, there can be multiple products associated with a specific barcode. If a user requests information associated with a specific barcode, information associated with the user or request can be used to attempt to determine the associated product if more than one matching product is uncovered. In some embodiments, a location of a user device at approximately a time of the request can be used to attempt to determine the appropriate product, such as if the user is in a store that only offers one of the potential products. Other information can be used as well, such as past locations, purchase history, viewing patterns, and the like.

Barcode disambiguation

Various embodiments provide methods and systems for users and business owners to share content and/or links to visual elements of a place at a physical location, and, in response to a user device pointing at a tagged place, causing the content and/or links to the visual elements of the place to be presented on the user device. In some embodiments, content and links are tied to specific objects at a place based at least in part upon one of Global Positioning System (GPS) locations, Inertial Measurement Unit (IMU) orientations, compass data, or one or more visual matching algorithms. Once the content and links are attached to the specific objects of the place, they can be discovered by a user with a portable device pointing at the specific objects in the real world.

Sharing links in an augmented reality environment

Various embodiments relating to predictive analytics from visual data are described. For example, a system associated with a matching service can obtain visual data that includes content related to a marketing campaign associated with a particular product or service. The system can determine image information that contains one or more objects relating to a logo for the particular brand or product. The system can process the content item using one or more machine vision algorithms. The system can determine usage data associated with the particular product or service based at least in part on the one or more feature descriptors. The system can aggregate the usage data with other usage data relating to different users across different time periods to compile a database of insight information with respect to the particular product or service. The system can determine one or more usage patterns relating to the particular product or service.

Predictive analytics from visual data

Systems and methods for displaying an image of a virtual object in an environment are described. A computing device is used to capture an image of a real environment including a marker. One or more virtual objects which do not exist in the real environment are displayed in the image based at least on the marker. The distance and orientation of the marker may be taken into account to properly size and place the virtual object in the image. Further, virtual lighting may be added to an image to indicate to a user how the virtual object would appear with the virtual lighting.

Improving advertisement relevance

Various approaches discussed herein enable augmenting an image of a person wearing an article of clothing to provide an augmented reality (i.e., virtual) article of clothing to a viewer in order to overlay, replace, and/or augment an actual article of clothing being worn by the user. The augmented reality article of clothing is positioned on the user's real-world piece of clothing according to various markings and/or data that allow the augmented reality article of clothing to appear as if it were being worn by the user, even during movement of the user.

Augmented reality fashion

Approaches enable images submitted by users, owner, and/or authorized person of a point of interest (e.g., a place, a scene, an object, etc.) to be used as a fiducial to assist recognition and tracking of the point of interest in an augmented reality environment. Multiple images (e.g., crowd-sourced images) of a point of interest taken from different points of view can be dynamically used. For example, as a user with a user device moves through a point of interest, a different image can be chosen from a set of stored candidate images of the point of interest based at least upon GPS locations, IMU orientations, or compass data of the user device. In this way, instead of relying on artificial fiducial images for various detection and tracking approaches, approaches enable images submitted by users and/or an owner or other authorized person of a point of interest to be used as fiducials to assist recognition and tracking of the point of interest.

Adaptive fiducials for image match recognition and tracking

Various embodiments provide methods and systems for detecting one or more segments of an image that are related to a particular object in the image (e.g., a logo or trademark) and extracting at least one feature point, each of which is represented by one feature point descriptor, based at least upon a contour curvature of the one or more segments. The at least one feature point descriptor can be converted into one or more codewords to generate a codeword database. A discriminative codebook can then be generated based upon the codeword database and utilized to detect objects and/or features in a query image.

Detection and recognition of objects lacking textures

Various approaches discussed herein enable providing a virtual reality experience of trying on clothes by augmenting an image of an article of clothing so that it appears to be worn by a particular person who is represented in a separate image. The image of the person wearing a special article of clothing containing a number of gridlines is analyzed along with an image of the special article of clothing as it appears unworn. The analysis includes calculating differences in the images to determine a change in the position of the gridlines between the images, then used to generate body shape data. The body shape data is used to augment an image of a prospective article of clothing, which modified image is then combined with the image of the person wearing a special article of clothing and displayed.

Augmented reality fitting approach

The subject technology provides embodiments for performing fast corner detection in a given image for augmented reality applications. Embodiments disclose a high-speed test that examines intensities of pairs of pixels around a candidate center pixel. In one example, the examined pairs are comprised of pixels that are diametrically opposite ends of a circle formed with the candidate center pixel. Further, a pyramid of images including four rings of surrounding pixels is generated. An orientation of the pixels from the four rings are determined and a vector of discrete values of the pixels are provided. Next, a forest of trees are generated for the vector of discrete values corresponding to a descriptor for a first image. For a second image including a set of descriptors, approximate nearest neighbors are determined from the forest of tree representing closest matching descriptors from the first image.

Fast interest point extraction for augmented reality

Methods, systems and computer program products for automatic color correction of image and video content are provided. A computer-implemented method may include generating an auto-level linear transform and a histogram equalization transform of a color distribution histogram for an original image among a set of sequential images. The auto-level linear transform and the histogram equalization transform are blended to create a modified image. Pixel color is adjusted in the modified image so that a color difference between a pixel and neighboring pixels in the modified image corresponds to a color difference between respective pixels in the original image.

Automatic color correction

Advertisement relevance

Systems and methods are provided herein relating to video classification. A trained classifier can analyze a video for suggested edits. A plurality of features of the video can be analyzed based that determines whether the video is a good candidate for various type of editing. The suggested edits can be performed automatically or with the authorization of a user who submitted the video. The user can review the edited video and either approve or reject the edits. Using an automated process to suggest and perform video edits can improve the quality of videos within a video data store.

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San Francisco, CA, United States of America

William Brendel