Database Reference
In-Depth Information
representation is a fi rst step in defi ning a full motion language, relating to the movement of
bodies as in the vocal channel of speech and the graphic channel of script.
The research contributes to several fi elds, such as knowledge representation and da-
tabases. It presents a formal and general model for the representation of raw motion data
that can be extended to the imitation of linguistic perceptions expressed through the motion
channel.
Several areas are suggested for further study. Since the motion model is represented
only by binary parameters, it has substantial raw data compression possibilities (Spiegler &
Maayan, 1985; Samet, 1984; Samet & Webber, 1988a; Samet & Webber, 1988b). A detailed
analogy between optical character recognition (OCR) and motion processing is needed
to extend the pattern recognition discipline to the fi eld of motion. Similarly, an analogy
between natural language processing (NLP) and motion processing will provide means
of recognizing and understanding motion words. We have shown a direction to defi ne a
motion building block. A fi nite number of precise, general, and generative building blocks
can be characterized in a well-defi ned motion world such as a robot motion environment
(Egerstedt, 2001), enabling the construction of words, sentences, and motion text about the
said motion world.
Binary representation of motion also opens the way to studies in diagnosis and measure-
ment of physiological phenomenon, such as motor disorders, changes in motor capabilities
under the effect of different medical treatments or drugs, athletic training, comparative
variations in motor capabilities of different individuals, as well as ways in which they carry
out motor tasks.
REFERENCES
Agarwal, P.K. et al. (2002). Algorimic issues in modeling motion.
ACM Computing Surveys,
34
(4), December.
Ariav, G. (1986). A temporally oriented data model.
ACM Trans. on Database Systems,
11
(4), December, 449-527.
Badler, N.I., & Smoliar, S.W. (1979). Digital representations of human movements.
ACM
Computing Surveys, 11
(1), March, 19-38.
Bruderlin, A., & Williams, L. (1995). Motion signal processing.
Computer Graphics Pro-
ceedings - SIGGRAPH95,
August, 97-104.
Calvert, T.W., & Chapman, J. (1982). Aspects of the cinematic simulation of human move-
ment.
IEEE CG&A
, November, 41-50.
Casavant, T.L., & Mukesh, S. (1994).
Readings in distributed computing systems.
USA:
IEEE Computer Society Press.
Calvert, T.W., Bruderlin, A., Dill, J., Schiphorst, T., & Welman, C. (1993). Desktop anima-
tion of multiple human fi gures.
IEEE CG&A,
May, 18-26.
Earnshaw, R., Mangnenat-Thalmann, N., Terzopoulos, D., & Thalmann, D. (1998). Computer
animation for virtual humans.
IEEE CG&A
, September/October, 20-23.
Egerstedt, M. (2001). Linguistic control of mobile robots
.
Proceedings of IEEE Conference
on Intelligent Robots and Systems, 2001, Maui, Hawaii,
877-882.
Eshkol, N., & Wachmann, A. (1958).
Movement notation
. Weidenfeld and Nicolson.
Etzion, O. et al. (Ed.). (1998).
Temporal databases: Research and practice
. Springer.
