Animal 3D reconstruction from videos

  • Author / Creator
    Ma, Youdong
  • 3D reconstruction of quadruped animals is a challenging problem, where key issues
    lie in their large shape variety and deformation within the same animal species as
    well as the lack of sufficient training data. In this thesis, we present two approaches
    toward this task. Our first approach is a model-based method called SMALF, where a
    parametric 3D shape template, SMAL, is employed to recover the 3D pose and shape
    of an animal from its raw video. On top of SMAL, our predicted mesh is further
    allowed to perform per-vertex deformations: this way, our proposed model benefits
    from the use of both parametric and non-parametric representations. Second, we
    present AnimalRecon, yet another method that uses a neural implicit function to
    represent 3D animal shapes. Neural implicit representation methods enjoy a higher
    degree of flexibility and expressiveness due to the continuous nature of this shape
    representation. However, how to extract a space-time coherent representation for
    a video can be difficult to achieve. First, we implement neural blend skinning, a
    method to enable our implicit shape to deform. Our implicit shape model is then
    fitted into the given video. Qualitative and quantitative results of our approach
    SMALF are conducted on two BADJA and RGBD-Dog datasets, where our method
    is demonstrated to improve over the baselines. Our method AnimalRecon is further
    examined on the RGBD-Dog dataset, where higher-fidelity 3D reconstruction results
    are shown when comparing with the existing efforts.

  • Subjects / Keywords
  • Graduation date
    Spring 2023
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.