# |3DS| Our Quiet Neighbour {% embed url="" %} In collaboration with the Wendy Walls, Naomi Mullumby, Joe Barrins and Melbourne General Cemetery. *The Melbourne General Cemetery exhibition showcases and links diverse material from the Library and Special Collections, enabling students and staff to explore the character and history of our “quiet neighbour” through a range of intriguing objects, including maps, plans, botanical samples and 3D scans. Exploring University collections as part of the curriculum sparks new modes of inquiry and brings a great richness to student work.* NExT Lab produced digital objects for the Pedestal platform mainly using a mixed Photogrammetry and terrestrial laser scanning (BLK 360) workflow through Reality Capture. Some handheld 3D scanning was used for smaller objects. *** ## **Photogrammetry x Terrestrial Laser Scanning** Reality Capture allows the combination of Terrestrial Scanning and Photogrammetry, leveraging the geometric realism of terrestrial scanning and the infilling potential and colour accuracy of photogrammetry. Reality Capture was used to proccess the combined data into web-appropriate mesh objects for viewing from within Pedestal. Blender was used for the final clean up and polishing of the models.
{% content-ref url="/pages/-LXbX3f3wa2\_LUQrAbRa" %} [3D Scanning at the NExT Lab](/next-lab/3d-scanning/digital-reconstruction-at-the-next-lab.md) {% endcontent-ref %} *** ## **Video Animation** Using a high quality version of the assets, they were converted back into point clouds for use in an animation. All animations and rendering were produced in Blender. {% embed url="" %} {% content-ref url="/pages/Oqkyd7a4oUmXrDsUOeVX" %} [Point Clouds and Blender](/next-lab/3d-scanning/guides/working-with-3d-scan-data/point-clouds-and-blender.md) {% endcontent-ref %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://ms-kb.msd.unimelb.edu.au/next-lab/case-studies-and-projects/or-3ds-or-our-quiet-neighbour.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.