A9.com, Inc.

Nityananda Jayadevaprakash

William Brendel

David Creighton Mott

Scott Paul Robertson

Arnab Sanat Kumar Dhua

Colin Jon Taylor

Kathy Wing Lam Ma

Mark Jay Nitzberg

Jie Feng

Douglas Ryan Gray

Xiaofan Lin

Edward Hsiao

Adam Neustein

Zur Nehushtan

Shruti Sheorey

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

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

Approaches provide for analyzing image data to determine and/or recognize text in the image data. The recognized text can be used to generate a search query that can be automatically submitted to a search engine without having to type the search query to identify a product (or related products) associated with the image. For example, a camera of a computing device can be used to capture a live camera view (or single images) an item. An application executing on the computing device (or at least in communication with the computing device) can analyze the image data of the live camera view to determine a set of keywords (e.g., identified text) based on visual features extracted from the image data. The keywords can be used to query an index of product titles, common search queries, among other indexed data to return a ranked list of search suggestions based on a relevance function. The relevance function can consider the ordering of the keywords to rank search suggestions more highly that contain the keywords having the same word order. Further, the relevance function can consider the confidence of the visual recognition of each keyword, the confidence of each search suggestion, customer impact, as well as other factors to determine the ranking of the search suggestions. The search suggestions can be further refined to ensure search results that the user will be more likely to view and/or purchase.

Visual search suggestions

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

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.

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San Jose, CA, United States of America

Nityananda Jayadevaprakash