Advances in Vision-Based Human Body Modeling - 3D Modeling and Animation: Synthesis and Analysis Techniques for the Human Body - page 2

intends to give an overview of the current techniques in order to help in the
selection of the most suitable method for a certain problem.
Introduction
Human body modeling is experiencing a continuous and accelerated growth. This
is partly due to the increasing demand from computer graphics and computer
vision communities. Computer graphics pursue a realistic modeling of both the
human body geometry and its associated motion. This will benefit applications
such as games, virtual reality or animations, which demand highly realistic
Human Body Models (HBMs). At the present, the cost of generating realistic
human models is very high, therefore, their application is currently limited to the
movie industry where HBM's movements are predefined and well studied
(usually manually produced). The automatic generation of a realistic and fully
configurable HBM is still nowadays an open problem. The major constraint
involved is the computational complexity required to produce realistic models
with natural behaviors. Computer graphics applications are usually based on
motion capture devices (e.g., magnetic or optical trackers) as a first step, in order
to accurately obtain the human body movements. Then, a second stage involves
the manual generation of HBMs by using editing tools (several commercial
products are available on the market).
Recently, computer vision technology has been used for the automatic genera-
tion of HBMs from a sequence of images by incorporating and exploiting prior
knowledge of the human appearance. Computer vision also addresses human
body modeling, but in contrast to computer graphics it seeks more for an efficient
than an accurate model for applications such as intelligent video surveillance,
motion analysis, telepresence or human-machine interface. Computer vision
applications rely on vision sensors for reconstructing HBMs. Obviously, the rich
information provided by a vision sensor, containing all the necessary data for
generating a HBM, needs to be processed. Approaches such as tracking-
segmentation-model fitting or motion prediction-segmentation-model fitting
or other combinations have been proposed showing different performances
according to the nature of the scene to be processed (e.g.. indoor environments,
studio-like environments, outdoor environments, single-person scenes, etc). The
challenge is to produce a HBM able to faithfully follow the movements of a real
person.
Vision-based human body modeling combines several processing techniques
from different research areas which have been developed for a variety of
conditions (e.g., tracking, segmentation, model fitting, motion prediction, the