Google Inc.

Ehud Rivlin

Dragomir Dimitrov Anguelov

Abhijit S Ogale

Mei Han

Erik Murphy-Chutorian

Shengyang Dai

Kyle Howard Heath

Scott E Lininger

Jay Yagnik

Charles Joseph Rosenberg

Gal Chechik

David Kogan

Asaf Zomet

Ameesh Makadia

Arthur Edmond Blume

Evangelos Kokkevis

Andrew Logan Harp

Won S Chun

Diego Ariel Gertzenstein

Rachel L Petterson

Anthony Gerald Francis

Maks Ovsjanikovs

Chuck Joseph Rosenberg

Methods and systems for interacting with multiple three-dimensional (3D) object data models are provided. An example method may involve receiving a search query comprising a descriptor for an object that is associated with a given category of objects. The method may involve comparing the descriptor to contents of a three-dimensional (3D) object-data-model database that includes contents associated with the given category of objects. Based on the comparison, the method may involve generating a search query result that comprises 3D object data models that describe the object and associated images that describe the object. The method may also involve arranging the 3D object data models and associated images in the search query result in a manner such that the 3D object data models are moveable inline in the search query result, and providing the search query result.

Searching three-dimensional (3D) object data models

A system, computer-implemented method and non-transitory computer-readable medium for automatically searching for images from events is provided. One or more personal identity tags are provided, wherein the personal identity tags relate to identification information for one or more individuals. Next, at least one event group is identified, wherein the event group is a collection of images associated with an event, the collection of images including one or more images tagged with one or more of the provided personal identity tags. A collection of the images for each of the identified event groups is then received.

Searching for events by attendants

A system and method for determining the location of a mobile device is provided. Such a method includes receiving an interior map, determining a first location to be an absolute location of a mobile communication device, locating the absolute location at a first position on the interior map, relocating the mobile communication device to a second location, estimating the second location of the mobile communication device based on an output of one or more sensors and modifying, using a computer-based system, the estimated second location based on a comparison of the estimated second location to the interior map.

Qualitative and quantitative sensor fusion for indoor navigation

Implementations relate to presenting search results to a user. In particular, disclosed techniques include presenting both image search results and 3D model search results to a user. The user can manipulate the 3D model depicted in the 3D model search results by rotating, translating or zooming. Implementations thus provide a rich synergistic exploration experience to the user.

Combining unstructured image and 3D search results for interactive search and exploration

Embodiments generally relate to summarizing a photo album in a social network system. In one embodiment, a method includes grouping photos into a plurality of groups of photos, and selecting a plurality of representative photos, where each representative photo represents a respective group from the plurality of groups, where the selecting is based on a quality score of each of the photos, and where each quality score is based on different types of attributes. The method also includes enabling the plurality of representative photos to be shared.

Summarizing a photo album in a social network system

Methods of and systems for determining a location of a mobile device using transmitted audio signals is provided. In an embodiment, meta data included in the audio signals may also be used. In an embodiment, a characteristic, such as a received signal strength, may be measured to determine the location of the mobile device.

Audio based localization

Methods and systems permit automatic matching of videos with images from dense image-based geographic information systems. In some embodiments, video data including image frames is accessed. The video data may be segmented to determine a first image frame of a segment of the video data. Data representing information from the first image frame may be automatically compared with data representing information from a plurality of image frames of an image-based geographic information data system. Such a comparison may, for example, involve a search for a best match between geometric features, histograms, color data, texture data, etc. of the compared images. Based on the automatic comparing, an association between the video and one or more images of the image-based geographic information data system may be generated. The association may represent a geographic correlation between selected images of the system and the video data.

Automatic video and dense image-based geographic information matching and browsing

Initial trajectory data that provides an initial description of an approximate trajectory of a device during a time period, and correction data that indicates a location of the device outside the approximate trajectory of the device within the time period, are received. A modified trajectory data that provides a modified description of a corrected trajectory of the device is generated. In particular, terms to express (i) location constraints that limit deformation of the approximate trajectory of the device and (ii) a modification constraint that limits departure of the corrected trajectory of the device from the location indicated by the correction data are generated, and the initial description of the approximate trajectory of the device is modified using the generated terms.

Automatic correction of trajectory data

Pose data includes multiple pose samples, where each pose sample indicates a reported location of a device at a respective time, and where the multiple pose samples describe a trajectory of the device. To correct the pose data, pose modification data for some of the pose samples is received, indicating respective modifications of the pose samples by a user. Several other pose samples are automatically modified in view of the received pose modification data. To automatically modify the pose samples, one or more user modification constraints are applied, where each user modification constraint seeks to preserve the modification of the location of the device for a respective pose sample. One or more location constraints are also applied, each of which seeks to preserve the reported location of the device for a respective pose sample. Modified pose data is generated in view of the user modification constraints and the location constraints.

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Palo Alto, CA, United States of America

Ehud Rivlin