Google Inc.

Stephen David Zelinka

Emil Constantin Praun

Chikai J Ohazama

Eli Brandt

Mohammed Waleed Kadous

Andrew Robert Kirmse

Charles C Rhodes

Randall Wilson

Nicholas Julian Pelly

Matthew Robert Simpson

Bailiang Zhou

Marc Stogaitis

Angana Ghosh

Jeff Brown

Elizabeth Hunt

Christopher Jay Wahlen

Chris Raykovich

Ying Y Su

Erika Rice Scherpelz

Reto Meier

Paul S Heckbert

Display screen with set of icons

Embodiments described herein may help to protect users' privacy when storing and/or utilizing location data that is provided by the users' mobile devices. An example method may involve: (a) determining a location history associated with a first client device, wherein the location history comprises a plurality of time-stamped location reports associated with the first client device, (b) before the location history is exported: (i) identifying at least one stop in the location history, wherein the at least one stop corresponds to a plurality of location reports that indicate a substantial lack of movement by the first client device, and (ii) scrubbing the location history in order to obscure at least one location report that corresponds to the at least one stop, and (c) exporting the scrubbed location history to long-term data storage.

Device location history anonymization based on stop decision

To determine the location of a querying mobile device, a request is received from the querying mobile device via a communication network. One or several participating mobile devices that potentially are physically proximate to the querying mobile device are identified. A request to scan for a location broadcast message transmitted by the querying mobile device is sent to the participating mobile devices. One or more location broadcast reports from participating mobile devices are received, where each received location broadcast report indicates that the location broadcast message was received at the corresponding participating mobile device. The location of the querying mobile device is estimated based on (i) the received one or more location broadcast reports and (ii) respective locations of the participating mobile devices from which the one or more location broadcast reports were received.

Using peer devices to locate a mobile device

Device location history anonymization based on stop detection

Methods and systems for grouping computing devices together based on the devices being colocated with one another or being associated with complementary usage contexts, and then using the location or usage context of one device in the group to estimate the location or usage context of another device in the group are described. An example method may include receiving first sensor data from sensors of a first computing device; receiving second sensor data from sensors of a second computing device; determining, based on the received sensor data, that the first and second computing devices are colocated with one another; identifying, based on the first sensor data, a context associated with the first computing device; and determining, based at least in part on the context associated with the first computing device, a context associated with the second computing device.

Systems and techniques for colocation and context determination

A mobile device receives signals from transmitting devices and generates sets of signal metrics based on the received signals. The mobile device also receives indicated locations, where each indicated location is associated with a respective set of signal metrics. The mobile device provides location-specific data to a transmitting device locating engine to estimate locations of the transmitting devices, where the location-specific data includes data representing the sets of signal metrics and data representing the indicated locations. The mobile device further receives an indication of sharing criteria via a user interface of the mobile device, and causes the estimated locations to be selectively shared with one or more other mobile devices based on the sharing criteria.

Creating and sharing private location databases

Assets of raw geo-located imagery can be divided into tiles and coverage masks can be generated for each tile. For each tile, fragments of pixels from coverage masks of neighboring tiles can be extracted and tagged. The fragments can be sorted and stored in a data structure so that fragments having the same tag can be grouped together in the data structure. The fragments can be used to feather the coverage mask of the tile to produce a blend mask. Multi-resolution imagery and mask pyramids can be generated by extracting fragments from tiles and minified (e.g., down-sampled). The minified fragments can be tagged (e.g., by ancestor tile name), sorted and stored in a data structure, so that fragments having like tags can be stored together in the data structure. The fragments can be assembled into fully minified tiles for each level in the pyramid.

Large-scale image processing using mass parallelization techniques

Certain embodiments of this disclosure include methods and devices for adjusting the precision of location information. According to one embodiment, a method is provided. The method may include: obtaining a request for location information from an application; determining that the location information needs to be adjusted; obtaining the location information; adjusting the location information, wherein the adjusting includes: (i) adding noise to the location information to obtain noisy location information, (ii) discretizing the noisy location information to obtain discretized location information, and (iii) hysteresizing the discretized location information to obtain adjusted location information. The adjusted location information may then be provided to the requesting application.

Methods and devices for adjusting the precision of location information

Embodiments of this invention relates to orthorectifying oblique imagery to a nadir view. In an embodiment, a method orthorectifies oblique photographic imagery. An oblique photographic image is projected onto a three-dimensional model of terrain. Points are sampled from the projected photographic image at the intersection of the three-dimensional model of terrain and parallel rays extended from a virtual viewport having a nadir perspective. The sampled points are assembled into an orthorectified image. Finally, the orthorectified image or the sampled points are adjusted approximately according to a difference in tilt angle between a camera that captured the oblique photographic image and the viewport having the nadir perspective to generate a foreshortened orthorectified image. Each location in the foreshortened orthorectified image corresponds linearly to a corresponding location in a two-dimensional map.

Orthorectifying stitched oblique imagery to a nadir view, and applications thereof

Assets of raw geo-located imagery can be divided into tiles and coverage masks can be generated for each tile. For each tile, fragments of pixels from coverage masks of neighboring tiles can be extracted and tagged. The fragments can be sorted and stored in a data structure so that fragments having the same tag can be grouped together in the data structure. The fragments can be used to feather the coverage mask of the tile to produce a blend mask. Multi-resolution imagery and mask pyramids can be generated by extracting fragments from tiles and minified (e.g., down-sampled). The minified fragments can be tagged (e.g., by ancestor tile name), sorted and stored in a data structure, so that fragments having like tags can be stored together in the data structure. The fragments can be assembled into fully minified tiles for each level in the pyramid. Input tiles in a first projection are re-projected into a second projection using techniques that minimize distortion in the re-projected imagery.

Methods and systems for updating mosaics of digital source images are disclosed. According to one embodiment, a method for updating a mosaic of digital source images includes segmenting the mosaic to regions, generating a plurality of region-statistics where each region-statistics correspond to image characteristics of one region, organizing the plurality of region-statistics in a database, and updating the mosaic using at least one target region-statistics from the organized plurality of region-statistics. Updating the mosaic can include color correcting. The method for updating a mosaic of digital source images can also includes optimizing the organized plurality of region-statistics, wherein the optimizing is based on one or more reference region-statistics from the organized plurality of region-statistics.

Enhancing digital image mosaics using region-statistics

An oblique photographic image is projected onto a three-dimensional model of terrain. Points are sampled from the projected photographic image at the intersection of the three-dimensional model of terrain and parallel rays extended from a virtual viewport having a nadir perspective. The sampled points are assembled into an orthorectified image. Finally, the orthorectified image or the sampled points are adjusted approximately according to a difference in tilt angle between a camera that captured the oblique photographic image and the viewport having the nadir perspective to generate a foreshortened orthorectified image. Each location in the foreshortened orthorectified image corresponds linearly to a corresponding location in a two-dimensional map.

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Los Gatos, CA, United States of America

Stephen David Zelinka