dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Panja, Deb | |
dc.contributor.author | Verhage, Lourens | |
dc.date.accessioned | 2024-07-24T23:05:51Z | |
dc.date.available | 2024-07-24T23:05:51Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/46888 | |
dc.description.abstract | This thesis outlines a new scene object isolation method that is capable of isolating centre scene objects from a set of images that captures the scene. Doing this
it shows some interesting quirks in the SMF data. The thesis experiments with
the different configurations for the object isolation method, and presents these
results. Beside this the thesis proposes some changes and extensions to Gaussian
splatting to enable it to optimize the isolated objects, and re-implements depthregularized Gaussian splatting. The modifications are explored by tweaking
their hyper parameters, and in doing so showing their influence on the accuracy
of the final trained object. The thesis is closed by speculating in possible improvements that could still be made to the object isolation method, and quickly
proposes a method that could be used to allow for multiple objects, from the
same scene, to be trained at the same time and be combined into one scene. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | Given an image set that captures a single scene, isolate an object in this scene using the images, and reconstruct the isolated object using 3D Gaussian splatting | |
dc.title | 3D Gaussian Splatting for Isolated Objects | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Image Processing | |
dc.subject.courseuu | Computing Science | |
dc.thesis.id | 34810 | |