Uber Technologies, Inc.

Microsoft Technology Licensing, LLC

Benjamin James Kadlec

Christopher D Moore

Aaron Matthew Rogan

Kapil Gupta

Christine Misuye Tao

Lionel Gueguen

Janice Jieun Suh

Jeremy Hintz

Susmit Biswas

Systems and methods are provided for generating sets of candidates comprising images and places within a threshold geographic proximity based on geographic information associated with each of the plurality of images and geographic information associated with each place. For each set of candidates, the systems and methods generate a similarity score based on a similarity between text extracted from each image and a place name, and the geographic information associated with each image and each place. For each place with an associated image as a potential match, the systems and methods generate a name similarity score based on matching the extracted text of the image to the place name, and store an image as place data associated with a place based on determining that the name similarity score for the extracted text associated with the image is higher than a second predetermined threshold.

Imagery evidence matching system

A system determines a set of POIs that are visible from a location. The system stores a visibility map for each POI. A visibility map includes data about locations or regions from which the associated POI is visible. The data may include information about how visible the POI is from different locations. The system divides a region into road bins (e.g., geofences a route passes through). Each road bin is associated with a set of POIs that are visible from locations within the road bin. When the system receives a request from a user device for information about visible POIs, the system determines a road bin that corresponds to the location of the user device, identifies POIs associated with the road bin, and transmits information about the set of POIs to the user device.

Displaying visible points of interest with a navigation system

Displaying visible points of interest with a navigating system

In scenarios involving the capturing of an environment, it may be desirable to remove temporary objects (e.g., vehicles depicted in captured images of a street) in furtherance of individual privacy and/or an unobstructed rendering of the environment. However, techniques involving the evaluation of visual images to identify and remove objects may be imprecise, e.g., failing to identify and remove some objects while incorrectly omitting portions of the images that do not depict such objects. However, such capturing scenarios often involve capturing a lidar point cloud, which may identify the presence and shapes of objects with higher precision. The lidar data may also enable a movement classification of respective objects differentiating moving and stationary objects, which may facilitate an accurate removal of the objects from the rendering of the environment (e.g., identifying the object in a first image may guide the identification of the object in sequentially adjacent images).

Object removal using lidar-based classification

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Boulder, CO, United States of America

Benjamin James Kadlec