🔊 Our yearly event around #ParaView in Europe is coming back! This upcoming edition will be a 3 days events: 23-24-25 September 2026 in Lyon, France. 👀 Sneak peeks of the program: - 💻 ParaView Hackathon on 23rd afternoon - 🗣️ Full Presentation Day and Dinner on 24th - 🛠️ Workshops on 25th morning As usual, everyone can contribute to the program and you are welcome to submit presentations, showcase your ParaView use cases and propose any community idea to make this day(s) a successful event! 🎉 Block your agenda 📅 and register here: https://lnkd.in/dWPfbkvv
Kitware Europe
Software Development
Villeurbanne, Auvergne-Rhône-Alpes 6,371 followers
Open source platforms and advanced solutions in visualization, image processing, computer vision & software process.
About us
We are proven leaders in the creation and support of open-source software. By leveraging our open source communities and our wide area of technical expertise, we are able to provide state of the art solutions for a host of complex technical problems.
- Website
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https://www.kitware.eu
External link for Kitware Europe
- Industry
- Software Development
- Company size
- 11-50 employees
- Headquarters
- Villeurbanne, Auvergne-Rhône-Alpes
- Type
- Privately Held
- Founded
- 2010
- Specialties
- Visualization, Computer Vision, Medical Imaging, and Software Process
Locations
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Primary
Get directions
6, Cours André Philip
Villeurbanne, Auvergne-Rhône-Alpes 69100, FR
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Get directions
28 Corporate Drive
Clifton Park, NY 12065, US
Employees at Kitware Europe
Updates
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🔥 Adjust Georeferenced 3D maps using navigation maps ! Recent developments have largely improved georeferencing maps in LidarView. 🗺️ LidarView now handles importing maps from Google Maps, Mapquest and OpenStreetMap. The SLAM in LidarView now also enables to modify specific trajectory points and recompute a coherent map that match them. This can be used to superimpose cartography to georeferenced 3D maps and rectify the trajectories thanks to them. The video shows how we can adjust the SLAM trajectory based on an OpenStreetMap tile to make it fit the road where the car was driving based on the map reprojection. 📖 More details in our blog post dedicated to georeferencing in LidarView : https://lnkd.in/dqKB7ttX 🙏 Data courtesy of the Autoware foundation: https://lnkd.in/eZhdn4y8 #SLAM #LidarView #Maps #OpenSource
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🛰️ Use satellite data to color your 3D map! Recent developments have largely improved georeferencing maps in LidarView. 🗺️ LidarView now handles importing maps from Google Maps, Mapquest and OpenStreetmap. ✨ The video below shows how to use satellite data (from MapQuest) to color a georeferenced 3D map built with a LiDAR sensor, fused in the SLAM with an INS (Inertial Measurement System) More details on georeferencing in LidarView in our recent blogpost: https://lnkd.in/dqKB7ttX 🙏 Data courtesy of the Autoware foundation: https://lnkd.in/eZhdn4y8 #SLAM #Surveys #LidarView #OpenSource
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📦ActiViz has officially been ported to ARM64 for both Linux and Windows! 🎉 ⚡Deploy ActiViz, the C# wrapper of VTK, to energy-efficient computing next generation of hardware! Read more about this milestone on our blog: https://lnkd.in/eE6xeRmV #ActiViz #ARM64 #ScientificVisualization #DataViz
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😀SLAM in LidarView now handles multiple LiDAR setups! 🗺️Multiple LiDAR sensors can be used together to cover a wider field of view and higher point density. LidarView now takes into account all the LiDAR frames from several sensors, and can estimate a single trajectory for the whole setup using SLAM algorithm. 🎬The video below shows how to create a high density map in LidarView using 3 sensors mounted on a bus. 🙏Data courtesy of the Autoware foundation: https://lnkd.in/eZhdn4y8 #SLAM #LidarView #Autoware #OpenSource
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🚀 #ParaView now offers a new transform filter with manual point matching! While the standard Transform filter is quick and easy to use, achieving high precision can sometimes be challenging. With Points Matching Transform, you can accurately position and align objects by manually placing and matching feature points between the source and the target. The filter then computes the transformation automatically for precise placement. 🎯 👉 Try it out by downloading the latest nightly build of ParaView: https://lnkd.in/eATKUSRp #kitware #registration #transform
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🤖ROS2 support in LidarView! 🔌LidarView can now connect to ROS2 live streams for point clouds, images, and odometry data, as well as replaying mcap files. ✨All LidarView tools can now be used on such a workflow : data analysis, SLAM, object detection and any custom filters. Do you need a custom visualizer for your ROS2 processes? Let us know! 🙏 Data courtesy of the Autoware foundation: https://lnkd.in/eZhdn4y8 #LidarView #SLAM #ROS2 #OpenSource #Autoware
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Download and run ParaView everywhere 🌐, even on HPC 🧑💻 with no GPUs capabilities at all! For a long time, there was a dedicated version of ParaView for headless HPC, now you can download a single binary package and deploy it everywhere even if: > There is no display 🖵 > There is no Xorg server installed 🖼️ > There is no GPU 🖥️ Indeed, ParaView pvserver does not use any rendering component directly anymore and just dynamically load whatever is available on your infrastucture, GLX libs, OpenGL, EGL or OSMesa! This will be fully available in ParaView 6.1.0, coming to you by april end! But you can download ParaView 6.1.0-RC2 binary release right now to test it! https://lnkd.in/eZ3rBAwk #ParaView #HPC #GPU #GLX #OpenGL #EGL
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🔍 Point cloud processing in ParaView / LidarView — algorithm overview (3/3) Continuing from our previous publication on the topic, the focus of today is on key processing steps frequently used to improve data quality and extract meaningful information: 🧹 Noise filtering and cleaning 🧩 Segmentation and shape analysis 🔗 Robust point cloud registration 🎯 These building blocks can be combined into flexible and reproducible processing pipelines, from raw acquisitions to structured and aligned results. More details in our blogpost : https://lnkd.in/d6C6-z7J If you have such data processing needs in your project, give it a try! #PointCloud #Paraview #LidarView #PCL #VESPA