Abstract: Human motion capture has become one of the major
area of interest in the field of computer vision. Some of the major
application areas that have been rapidly evolving include the
advanced human interfaces, virtual reality and security/surveillance
systems. This study provides a brief overview of the techniques and
applications used for the markerless human motion capture, which
deals with analyzing the human motion in the form of mathematical
formulations. The major contribution of this research is that it
classifies the computer vision based techniques of human motion
capture based on the taxonomy, and then breaks its down into four
systematically different categories of tracking, initialization, pose
estimation and recognition. The detailed descriptions and the
relationships descriptions are given for the techniques of tracking and
pose estimation. The subcategories of each process are further
described. Various hypotheses have been used by the researchers in
this domain are surveyed and the evolution of these techniques have
been explained. It has been concluded in the survey that most
researchers have focused on using the mathematical body models for
the markerless motion capture.
Abstract: In this paper we report a study aimed at determining
the most effective animation technique for representing ASL
(American Sign Language) finger-spelling. Specifically, in the study
we compare two commonly used 3D computer animation methods
(keyframe animation and motion capture) in order to ascertain which
technique produces the most 'accurate', 'readable', and 'close to
actual signing' (i.e. realistic) rendering of ASL finger-spelling. To
accomplish this goal we have developed 20 animated clips of fingerspelled
words and we have designed an experiment consisting of a
web survey with rating questions. 71 subjects ages 19-45 participated
in the study. Results showed that recognition of the words was
correlated with the method used to animate the signs. In particular,
keyframe technique produced the most accurate representation of the
signs (i.e., participants were more likely to identify the words
correctly in keyframed sequences rather than in motion captured
ones). Further, findings showed that the animation method had an
effect on the reported scores for readability and closeness to actual
signing; the estimated marginal mean readability and closeness was
greater for keyframed signs than for motion captured signs. To our
knowledge, this is the first study aimed at measuring and comparing
accuracy, readability and realism of ASL animations produced with
different techniques.
Abstract: In this paper we intend to ascertain the state of the art on multifingered end-effectors, also known as robotic hands or dexterous robot hands, and propose an experimental setup for an innovative task based design approach, involving cutting edge technologies in motion capture. After an initial description of the capabilities and complexity of a human hand when grasping objects, in order to point out the importance of replicating it, we analyze the mechanical and kinematical structure of some important works carried out all around the world in the last three decades and also review the actuators and sensing technologies used. Finally we describe a new design philosophy proposing an experimental setup for the first stage using recent developments in human body motion capture systems that might lead to lighter and always more dexterous robotic hands.