Impact of Data Capture Methods on 3D Reconstruction with Gaussian Splatting

This study examines how different filming techniques can enhance the quality of 3D reconstructions with a particular focus on their use in indoor crime scene investigations. Using Neural Radiance Fields (NeRF) and Gaussian Splatting, we explored how factors like camera orientation, filming speed, data layering, and scanning path affect the detail and clarity of 3D reconstructions. Through experiments in a mock crime scene apartment, we identified optimal filming methods that reduce noise and artifacts, delivering clearer and more accurate reconstructions. Filming in landscape mode, at a slower speed, with at least three layers and focused on key objects produced the most effective results. These insights provide valuable guidelines for professionals in forensics, architecture, and cultural heritage preservation, helping them capture realistic high-quality 3D representations. This study also highlights the potential for future research to expand on these findings by exploring other algorithms, camera parameters, and real-time adjustment techniques.

Authors

Institutions

Publication Details

Journal
Journal of Imaging
Published
2025-02-18
DOI
https://doi.org/10.3390/jimaging11020065
Citations
5
Primary Topic
Image Processing and 3D Reconstruction
Type
article
Field-Weighted Citation Impact
6.38

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of Data Capture Methods on 3D Reconstruction with Gaussian Splatting

Radoslav Iliev Miltchev, Maurice van Keulen, Dimitar Rangelov, Sierd Waanders et al.
5 citations
Journal of Imaging
Image Processing and 3D Reconstruction
6.38
article

Impact of Data Capture Methods on 3D Reconstruction with Gaussian Splatting

Radoslav Iliev Miltchev, Maurice van Keulen, Dimitar Rangelov, Sierd Waanders, Kars Waanders
article en
5 citations

Abstract

This study examines how different filming techniques can enhance the quality of 3D reconstructions with a particular focus on their use in indoor crime scene investigations. Using Neural Radiance Fields (NeRF) and Gaussian Splatting, we explored how factors like camera orientation, filming speed, data layering, and scanning path affect the detail and clarity of 3D reconstructions. Through experiments in a mock crime scene apartment, we identified optimal filming methods that reduce noise and artifacts, delivering clearer and more accurate reconstructions. Filming in landscape mode, at a slower speed, with at least three layers and focused on key objects produced the most effective results. These insights provide valuable guidelines for professionals in forensics, architecture, and cultural heritage preservation, helping them capture realistic high-quality 3D representations. This study also highlights the potential for future research to expand on these findings by exploring other algorithms, camera parameters, and real-time adjustment techniques.

Journal of ImagingVol. 11(2)
Saxion (NL), Technical University of Sofia (BG), Politieacademie (NL), University of Twente (NL)
University of Twente
Sustainable cities and communities
Openalex Percentile: Top 4%
Image Processing and 3D Reconstruction
6.38
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Impact of Data Capture Methods on 3D Reconstruction with Gaussian Splatting — Radoslav Iliev Miltchev, Maurice van Keulen, et al. · Journal of Imaging (2025) | TGRS Research Map | TGRS