Advances in Vision-Based Human Body Modeling - 3D Modeling and Animation: Synthesis and Analysis Techniques for the Human Body - page 11

is established in order to locate the subject. Tracking through consecutive frames
commonly incorporates prediction of movement, which ensures continuity of
motion, especially when some body parts are occluded. Some techniques focus
on tracking the human body as a whole, while other techniques try to determine
the precise movement of each body part, which is more difficult to achieve, but
necessary for some applications. Tracking may be classified as 2D or 3D. 2D
tracking consists in following the motion in the image plane either by exploiting
low-level image features or by using a 2D human model. 3D tracking aims at
obtaining the parameters, which describe body motion in three dimensions. The
3D tracking process, which estimates the motion of each body part, is inherently
connected to 3D human pose recovery. However, tracking either 2D or 3D may
also comprise a prior, but significant, step to recognition of specific movements.
3D pose recovery aims at defining the configuration of the body parts in the 3D
space and estimating the orientation of the body with respect to the camera. Pose
recovery techniques may be roughly classified as appearance-based and model-
based. Our survey will mainly focus on model-based techniques, since they are
commonly used for 3D reconstruction. Model-based techniques rely on a
mathematical representation of human body structure and motion dynamics. The
type of the model used depends upon the requisite accuracy and the permissible
complexity of pose reconstruction. Model-based approaches usually exploit the
kinematics and dynamics of the human body by imposing constraints on the
model's parameters. The 3D pose parameters are commonly estimated by
iteratively matching a set of image features extracted from the current frame
with the projection of the model on the image plane. Thus, 3D pose parameters
are determined by means of an energy minimization process.
Instead of obtaining the exact configuration of the human body, human motion
recognition consists of identifying the action performed by a moving person.
Most of the proposed techniques focus on identifying actions belonging to the
same category. For example, the objective could be to recognize several aerobic
exercises or tennis strokes or some everyday actions, such as sitting down,
standing up, or walking.
Next, some of the most recent results addressing human motion tracking and 3D
human pose recovery in video sequences, using either one or multiple cameras,
are presented. In this subsection, mainly 3D model-based tracking approaches
are reviewed. The following subsection introduces whole-body human motion
recognition techniques. Previous surveys of vision-based human motion analysis
have been carried out by Cédras & Shah (1995), Aggarwal & Cai (1999), Gavrila
(1999), and Moeslund & Granum (2001).