Pointfuse Showcases Autodesk BIM integration and New Point Cloud Software at SPAR 3D

London, 04 June 2018 – Pointfuse will demonstrate how its point cloud software bridges the gap between reality capture and digital construction at SPAR 3D Expo (5-7 June, Anaheim Conference Centre, California). The latest developments being shown for the first time include recently-announced Autodesk BIM 360 integration, a ground-breaking auto classification feature and a new cloud-based data processing platform called Pointfuse Bolt.

Pointfuse, intelligent mesh models not only provide selectable geometry but are highly optimised, reducing the working data size a factor of up to 100x, making them significantly easier to use and share with online 3D collaboration portals. With automatic segmentation of the mesh into discrete, selectable surfaces, a significant bottleneck is eliminated in the modelling process, speeding workflows with repeatable, consistent results.

A key highlight at SPAR 3D is the new Pointfuse integration with Autodesk’s BIM platform. This allows ‘as built’ models to be easily incorporated into BIM workflows managed with Autodesk BIM 360 which is the first single project platform connecting design through construction.

The new auto classification feature meanwhile dramatically speeds up the ability to classify objects within Pointfuse, both horizontal and vertical planar surfaces are automatically detected and separated into layers making further classification of objects faster and easier. Being able to quickly compare specific as-built objects and designs without having to run clash detection on a full model or point cloud, saves both processing time and man hours, reducing the number of false and irrelevant clashes being flagged.

The other key development being announced is Pointfuse Bolt which transforms converting point cloud data to 3D intelligent mesh models, utilising the latest cloud-based technology. It provides a scalable solution to process unlimited point clouds, from any source, of any size or scale in a matter of minutes.

“SPAR 3D is the perfect opportunity to showcase the new developments we have been working on within Pointfuse, introducing them to the market and get real world end-user feedback” commented Mark Senior, Regional Sales Director at Pointfuse. “SPAR 3D will also allow us to cement existing connections and forge new relationships within the 3D industry.”

SPAR 3D Expo & Conference brings together the top hardware, software, and visualization solution providers from across the globe for three action-packed days of education, exhibits, and live demonstrations. SPAR 3D is the only vendor neutral, cross industry 3D event in the market and this year is co-located with the AEC NEXT technology expo and conference. Taking place from the 5-7 June 2018 at the Anaheim Conference Centre, Anaheim, California SPAR 3D will feature 100 plus practical, engaging talks, dozens of cutting edge demonstrations, 120 exhibitor booths – including Pointfuse on booth 627, and more than a 1,000 3D innovators.

About Pointfuse
Pointfuse is a powerful modeling engine that delivers an automatic, precise and flexible way of converting the vast point cloud datasets generated by laser scanners or photogrammetry into segmented mesh models. Pointfuse uses advanced statistical techniques to create 3D models where individual surfaces can be selected and classified as new layers in the Pointfuse environment and exported to IFC and FBX for manipulation in any industry-standard CAD system. Offering ‘selectable surfaces’, Pointfuse V3 provides a unique approach. Surfaces within the 3D mesh models produced by Pointfuse V3 can now be identified, grouped and classified. These advancements within Pointfuse V3 bring a catalyst to the workflow of design and engineering projects, offering efficiencies that have not been possible when working with point clouds or traditional mesh models. Pointfuse V3 also significantly reduces the file size of 3D models created from point clouds. In simple terms, the data density within each surface is reduced whilst still maintaining the fidelity of the model. This results in a reduction in model size by a factor of ten, making ongoing use of the model easier, faster and more efficient. www.pointfuse.com