| Summary: | 碩士 === 國立臺灣大學 === 資訊工程研究所 === 81 === Superquadric models with parametric deformations (including
tapering, bending, and cavity deformation, etc.) are suitable
models to be used as solid primitives for describing a
complicated 3-D shape. This representation scheme is widely
used in applications of computer vision and computer graphics
during the past decade. Some different methods for recovery of
superquadric primitives from range images have already been
proposed. But effective distance measures between two
superquadric models for the matching task in 3-D object
recognition systems are still deficient. All available metrics
are error-of-fit measures between a set of range points and a
superquadric surface, used by recovery procedures. In this
thesis, we propose a distance measure to evaluate the degree of
shape similarity between two arbitrary 3-D object models. This
distance measure is proved to be a metric. The value of this
metric is based on the computation of the minimal total volume
of regions bounded between two 3-D object's surfaces. With nice
mathematical properties, superquadric models are very suitable
for the computation of this metric. Experimental results
demonstrate that this metric is effective for matching a
recovered superquadric with a database of superquadric models.
|
|---|
