Palantir Technologies Inc.

Andrew Elder

Peter Wilczynski

Ashley Einspahr

Anand Gupta

Daniel Patrick Cervelli

John Antonio Carrino

Kevin Ng

Reese Glidden

Alexander Mark

Sharon Hao

Andrew Moreland

Clare Adrien

Timothy James Slatcher

Jiawei Marvin Sum

Quentin Spencer-Harper

Robert Imig

Paul Ryan

Praveen Kumar Ramalingam

Guan Da Wang

Leah Anderson

Timothy Wilson

Gregory Martin

Ryan Zheng

Ryan Beiermeister

Jessica Headrick

Eric Knudson

Christopher Richbourg

Joshua Zavilla

Daniel O'Malley

John Kenneth Garrod

Matthew Fedderly

Jeffrey Bagdis

Kendra Knittel

Jasmine Peterson

Brandon McCain

Joseph Kruse

Parvathy Menon

Jack Grossman

Joseph Rafidi

Adam Storr

Brian H Hamilton

Cooper Bills

Hannah Korus

William Rhyne

Walker Burgin

Caitlin Colgrove

Xinyi Wang

Aditya Dahiya

Roger Chen

Matthew Gerhardt

Michael Barone

Matthew Bango

Ryan Xie

Claire Adrien

Roxana Nadrag

Mark Montoya

Eli Rosofsky

Alisa Le

Ezra Zigmond

Jocelyn Rivero

Bradley Engel

Marc Frankel

David Cohen

Joel Ossher

Timothy Yousaf

Brandon Marc-Aurele

Eric Jeney

David Montague

Kevin Zhang

Daniel Lidor

Westin Miller

Daniel Cervelli

Cassandra Wang

Vincent Tilson

Allen Chang

Andrew Lampert

Timothy Slatcher

Lucas Leighton Nunno

Peter Austin

Lucas Nunno

Daniel; Cervelli

In some embodiments, a method comprises obtaining a video stream of a portion of a geographic area, the video stream comprising a plurality of video frames, each of the plurality of video frames captured at a respective first time. Contextual metadata is obtained, the contextual metadata associated with one or more objects located in the portion of the geographic area at a second time, the second time being before each of the respective first times. The contextual metadata is inserted into one or more of the plurality of video frames, thereby causing the contextual metadata associated with the one or more objects to be overlaid on one or more corresponding portions of the one or more of the plurality of video frames.

Systems and methods for generating augmented reality content

Systems, methods, and non-transitory computer readable media are provided for displaying and annotating map-based geolocation data at an augmented reality (AR) headset. Users with access to the map-based geolocation data can create or confirm annotations for geospatial data that may be sent to the server computer and transmitted back to the headset of the user as well as different AR headsets associated with other users.

Contextual augmentation of map information using overlays

Systems and methods are provided for improved graphical user interfaces. The system enables multiple separate applications, each of which may typically be in their own separate window or tab, to be interacted within a single window, such as a tab of a web browser application. The main window includes smaller sub-windows that can correspond to a distinct application with its own graphical user interface. A large sub-window within the main window is opened for the primary application where the user is currently interacting with a graphical user interface of the primary application. The user then is able to switch between applications (all within the same main window) and applications that are no longer being used can be minimized in smaller sub-windows off to the side of the primary sub-window. The system enables a user to drag and drop an item from one sub-window to another sub-window. Some of the interactions between the windows and data transformations are stored and can be visually presented in a graph.

Graphical user interface system

Systems, methods, and non-transitory computer readable media are provided for generating or obtaining situations in which scores indicative of a danger or a hazard exceeds a threshold, receiving a selection of a first situation, in response to receiving the selection of the first situation, obtaining intelligence data, asset data, and operational data, analyzing the intelligence data using a trained machine learning model for the first situation; and determining a response measure based on the analyzed intelligence data.

Contextual scenario assessment

An example method of determining geolocations of composite entities based on information retrieved from heterogeneous data sources comprises: identifying, by a computer system, an association of a first object and a second object with a composite object; receiving, from a first data source associated with the first object by an ontology, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the first object; receiving, from a second data source associated with the second object by the ontology, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the second object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the composite object and a corresponding time identifier.

Determining geolocations of composite entities based on heterogeneous data sources

Display screen or portion thereof with graphical user interface

Systems, methods, and non-transitory computer readable media may provide a view of geospatial information. A user's selection of a location may be obtained. Characteristic information describing characteristics of the location may be obtained. Activities information describing activities of the location may be obtained. An interface (e.g., user interface, API) enabling presentation of a geospatial view of the activities of the location with respect to the characteristics of the location may be provided.

Systems and methods for providing a view of geospatial information

Methods, systems, and non-transitory computer readable media configured to display a geographical map overlaid with a marker layer comprising at least one marker; receive input from a user to change a zoom level of the geographical map from a first map scale to a second map scale; display the geographical map at the second map scale; and overlay the marker layer at the second map scale with the at least one marker at a second marker size. The second marker size is determined based on a correlation between the second map scale and the second marker size, in which (i) the second marker size is increased or decreased in the same direction as the second map scale when the second map scale is within a range from a low threshold point to a high threshold point, and (ii) a ratio change between two adjacent marker sizes is smaller than a ratio change between two corresponding adjacent map scales when the second marker size is outside the range from the low threshold point to the high threshold point.

Dynamic scaling of geospatial data on maps

Systems and methods are provided for generating and storing data snippets. A data file can be obtained from a data source through a plug-in interface. The data file can be played to a user through an application running on a computing device. An indication can be received from the user, through the application, to tag an entity depicted in the data file during playback of the data file. A snippet of the data file can be stored, wherein the snippet is a portion of the data file corresponding to the entity tagged by the user.

Systems and methods for generating, analyzing, and storing data snippets

Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.

Systems and methods for coherent monitoring

Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.

Tracked entity detection validation and track generation with geo-rectification

An example method of determining geolocations of objects based on information retrieved from heterogeneous data sources comprises: receiving, from a first data source associated with an object by an ontology-defined relationship, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the object; receiving, from a second data source associated with an object by an ontology-defined relationship, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the object and a corresponding time identifier.

Determining object geolocations based on heterogeneous data sources

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New York, NY, United States of America

Andrew Elder