Advanced 3D Gaussian Splatting with statistical linearization

Forschungsthema/Bereich

Computer science

Typ der Abschlussarbeit

Bachelor / Master

Startzeitpunkt

-

Bewerbungsschluss

31.01.2027

Dauer der Arbeit

6 months

Beschreibung

3D Gaussian Splatting (3DGS) has recently revolutionized the field of novel view synthesis by offering state-of-the-art rendering quality at real time speeds using only 2D images. By representing 3D scenes as a collection of anisotropic 3D Gaussians, it circumvents the high computational costs of traditional neural radiance fields.

However, the current mathematical formulation has limitations. To project these 3D Gaussians onto a 2D image plane, 3DGS explicitly linearizes the nonlinear perspective projection by applying a first-order Taylor series expansion around the Gaussian mean. This local affine approximation introduces projection errors, especially for highly distorted camera models or at the edges of the field of view.

In this thesis, a novel approach will be developed inspired by the field of nonlinear state estimation. Instead of relying on a first-order Taylor expansion, this project will use statistical linearization to approximate the projection. This should enhance reconstruction quality by reducing projection errors and enable highly distorted camera models.

Voraussetzung

Voraussetzungen an Studierende

• Students with a background in computer science, mathematics, electrical engineering, mechatronics or other engineering majors. It requires a high level of motivation and the ability to work independently and in a structured manner. Prior knowledge of computer graphics, Python and (CUDA) would be helpful but are not essential.

Studiengangsbereiche

• Ingenieurwissenschaften
  Elektrotechnik & Informationstechnik
  Geodäsie & Geoinformatik
  Informatik
  Maschinenbau
  Mechatronik & Informationstechnik
  Optics & Photonics
  Mobilität und Infrastruktur
  Mechanical Engineering
  Mobility Systems Engineering and Management
  Remote Sensing and Geoinformatics
  Information System Engineering and Management
  Computer Science
  Electrical Engineering and Information Technology
  Mechatronics and Information Technology
  Medizintechnik
  Photon Science and Technology
• Naturwissenschaften und Technik
  Mathematik
  Physik
  Technomathematik
  Physics
  Wirtschaftsmathematik

Betreuung

Titel, Vorname, Name

Jiachen Zhou

Organisationseinheit

Institut für Anthropomatik und Robotik (IAR) - Intelligent Sensor-Actuator-Systems (ISAS)

E-Mail Adresse

jiachen.zhou@kit.edu

Link zur eigenen Homepage/Personenseite

Website

Bewerbung per E-Mail

Bewerbungsunterlagen

• Lebenslauf
• Notenauszug

E-Mail Adresse für die Bewerbung
Senden Sie die oben genannten Bewerbungsunterlagen bitte per Mail an jiachen.zhou@kit.edu


Zurück