OpenTopography Tool Registry

The OpenTopography Tool Registry provides a community populated clearinghouse of software, utilities, and tools oriented towards high-resolution topography data (e.g. collected with lidar technology) handling, processing, and analysis. Tools registered below range from source code to full-featured software applications. We welcome contributions to the registry via the Contribute a Tool page.

Appearance of a tool in the OpenTopography Tool Registry does not imply endorsement, recommendation, or support, by the NSF OpenTopography Facility and is meant simply as a service to our users. OpenTopography does not guarantee the completeness or accessibility of specific content and links contributed by users. If you have been directly involved with the development of a registered tool and are not the original contributor of the tool to the registry, please email info@opentopography.org to supply updates or modifications to its entry.
Date   Tool Name Tool Type Keywords Rating
19 Mar 2015 Civil Maps

Description: Civil Maps allows users to upload their survey data, then specify the assets of interest and mapping specification. Upon upload, Civil Maps indexes all of the spatial information as defined in the mapping specification into a query-able format. The maps can then be dynamically generated on demand and exported to various tools such as AutoDesk Map3D from Civil Maps, which is useful for integrating into the customers workflow. The biggest pain point in the industry is the time to annotate 3D scans. Currently, processing huge 3D survey datasets is limited by the point­ and ­click annotation speed of the user and the limited resources of the users computer (I/O, CPU, Network, Memory).

By circumventing these bottlenecks, Civil Maps is introducing a paradigm shift in the workflow of annotating 3D survey data. Advancements in parallel computing and deep learning allows Civil Maps to reduce 2 years of manual annotation work down to 2 days of processing using our cloud infrastructure

 
Visualization, Point Cloud Analysis, Data Management / Handling deep learning, artificial intelligence, point cloud streaming protocol
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