Abstract (EN):
Human motion analysis from images is meticulously related to the
development of computational techniques capable of automatically identifying,
tracking and analyzing relevant structures of the body. This work explores the
identification of such structures in images, which is the first step of any computational
system designed to analyze human motion. A widely used database
(CASIA Gait Database) was used to build a Point Distribution Model (PDM) of the
structure of the human body. The training dataset was composed of 14 subjects
walking in four directions, and each shape was represented by a set of 113 labelled
landmark points. These points were composed of 100 contour points automatically
extracted from the silhouette combined with an additional 13 anatomical points
from elbows, knees and feet manually annotated. The PDM was later used in the
construction of an Active Shape Model, which combines the shape model with gray
level profiles, in order to segment the modelled human body in new images. The
experiments with this segmentation technique revealed very encouraging results as
it was able to gather the necessary data of subjects walking in different directions
using just one segmentation model.
Language:
English
Type (Professor's evaluation):
Scientific
Contact:
www.fe.up.pt/~tavares
No. of pages:
10
License type: