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Advancements in 3D Reconstruction and Collision Detection Technologies

This overview highlights the current status and future aspirations of advanced technologies in 3D reconstruction and collision detection. Under the new leadership of Meitian Wang, we are testing the Prigo3 hardware with successful dataset collection and alignment. State-of-the-art software is being developed for collision detection and 3D reconstruction using visible light images and silhouette carving techniques. Future plans include integrating augmented reality to enhance user experience, automate sample alignment, and facilitate real-time collision avoidance in goniometry, streamlining experimental processes.

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Advancements in 3D Reconstruction and Collision Detection Technologies

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Presentation Transcript

  1. Overview • Current status • New group leader: Meitian Wang • - Platre screening on 6D • Pilatus 6M on 10S • - hardware: Prigo3 on X06DA • - software: collision detection • for self shadow detection • - software: 3D reconstruction with visible • light images • Plans/wishes

  2. Current status of Prigo3 - tested in week 36 - successfully collected aligned datasets - small sphere of confusion  =  = 0  close to 90 degs

  3. Current status of software development – Collision detection engine - found computer science experts - collision detection as a generalised tool -> not only for collision detection of goniometers -> code optimised for GPGPU

  4. Current status of software development – 3D reconstruction of crystals - 3D reconstruction with visible light images -> silhouette carving -> optimised in OpenCV image edge detection 3D reconstruction

  5. Plans/wishes Augmented reality (AR) to assist user's experiments seamlessly – automatically and in real-time Execute grid scan and indexing processing Mount and align the sample automatically superimpose the result such as sample info from the DB, crystal orientation, better points to expose allow users to align the sample interactively and calculate possible collisions/stats for the given goniometry in background/real-time indicate smart strategies

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