Docsity
Docsity

Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity


Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan


Guidelines and tips
Guidelines and tips

Laban Movement Analysis: Analyzing & Generating Affective Movement for Artificial Agents, Summaries of Dance

This paper explores the potential of Laban Movement Analysis (LMA) as a precise and systematic structure for observing, describing, and generating expressive movement for artificial agents such as robots, animations, and kinetic sculptures. The authors, Sarah Jane Burton and her team, aimed to develop a common language between interdisciplinary research team members from the dance/choreography and engineering communities to facilitate affective movement recognition and generation. LMA, a comprehensive approach for observing and describing movement, was hypothesized to be an excellent candidate for deriving a low-dimensional representation of movement that facilitates affective motion modeling.

Typology: Summaries

2021/2022

Uploaded on 09/27/2022

jacksonhh
jacksonhh 🇬🇧

4.2

(23)

251 documents

1 / 8

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
92 LIVING ARCHITECTURE SYSTEMS GROUP WHITE PAPERS 2016
The Value and Use of Laban
Movement Analysis in
Observation and Generation
of Affective Movement
SARAH JANE BURTON
Sheridan College
This paper discusses Laban Movement Analysis (LMA) and its potential as a
comprehensive and precise structure for analyzing and representing expres-
sive movement. This can be of great use for characterizing and generating
affective movement for artificial agents, such as robots, animations, kinetic
sculptures and environments. In our collaborative work, “Laban Movement
Analysis and Affective Movement Generation for Robots
and Other Near-Living Creatures,”1 our goal was to generate compact, infor-
mative representations of movement to facilitate affective movement recogni-
tion and generation for robots and other artificial embodiments. We hypoth-
esized that LMA, a systematic and comprehensive approach for observing
and describing movement, is an excellent candidate for deriving a low-dimen-
sional representation of movement that facilitates affective motion modeling.
pf3
pf4
pf5
pf8

Partial preview of the text

Download Laban Movement Analysis: Analyzing & Generating Affective Movement for Artificial Agents and more Summaries Dance in PDF only on Docsity!

92 LIVING ARCHITECTURE SYSTEMS GROUP WHITE PAPERS 2016

The Value and Use of Laban

Movement Analysis in

Observation and Generation

of Affective Movement

SARAH JANE BURTON

Sheridan College

This paper discusses Laban Movement Analysis (LMA) and its potential as a comprehensive and precise structure for analyzing and representing expres- sive movement. This can be of great use for characterizing and generating affective movement for artificial agents, such as robots, animations, kinetic sculptures and environments. In our collaborative work, “Laban Movement Analysis and Affective Movement Generation for Robots and Other Near-Living Creatures,”^1 our goal was to generate compact, infor- mative representations of movement to facilitate affective movement recogni- tion and generation for robots and other artificial embodiments. We hypoth- esized that LMA, a systematic and comprehensive approach for observing and describing movement, is an excellent candidate for deriving a low-dimen- sional representation of movement that facilitates affective motion modeling.

In addition to the longstanding research on movement analysis in the dance community, affective movement analysis has more recently received signifi- cant attention in other domains. There is a large and active research effort on affective movement perception, recognition and generation in cognitive science, psychology, and affective computing.^2

Daily we consciously and subconsciously interpret meaning and self-expres- sion by observing body language of others. Our motivation for this research was the question, is it possible to translate emotional expression through an arm movement via algorithms, into a moving sculpture “with feelings”? Our inspiration was one of the immersive, responsive sculptures in a series entitled: Hylozoic Ground, by Philip Beesley and Rob Gorbet. Since people move in response to the sculpture, would it be possible to observe their movements and interact affectively through movement? This capability may be valuable beyond artistic installations, in applications such as human- computer interaction and human-robot interaction. Our goal then was to develop a way to translate between the movement language of humans and the potential movement language of the sculpture.

As a path to reach our goal, our research focused on expressive human ges- tures of the arm and hand, the parts of the body that would be most similar to the sculpture’s moving fronds. Each individual has a unique personal history that influences their movements, as does their physical “architecture” and ability. The challenge of this study, this partnership between the science of robotics and the art of expressive movement, was to attempt to discover and distil the essence of affective movement. The engineers looked to the dance/theatre performance world, where choreographed movements can be specific and repeatable with believable expressive qualities, for a language to analyze and describe movement.

Our approach aimed to quantify and formalize the relationship between perceived movement qualities and measurable features of movements, to enable this relationship to be exploited for automated recognition and generation of affective movement. Another challenge of our research was to develop a common language and shared understanding of movement analysis between interdisciplinary research team members from the dance/ choreography and engineering communities.

o,FDQnWGRPXFKIRU\RXXQWLO\RXNQRZKRZWRVHHp -RVÃGH&UHHIWVFXOSWRU

BURTON THE VALUE AND USE OF LABAN MOVEMENT ANALYSIS 95

The implication is that if something cannot be measured then it is qualita- tive and unprovable. The concepts in LMA are governed by principles, whether or not they are measurable, that Kagan asserts make them “con- crete, observable, experientially verifiable, repeatable and predictable.”^5 For this reason, we believe LMA is amenable to computational analysis and can be related to measurable features of movement.

Laban Movement Analysis employs a multilayered description of move- ment, focusing on the components: Body, Space, Effort and Shape. Body indicates the active body parts, and the sequence of their involvement in the movement; Space defines where in space the movement is happening, the directions, spatial patterns and range; Effort describes the inner atti- tude toward the use of energy; and Shape characterizes the bodily form, and its changes in space. If each of these aspects is understood in terms of its own integrity, one can begin to comprehend how each interacts and illu- minates the others. 5 Irmgard Bartenieff (1890–1981), a colleague of Laban, advocates the use of Effort and Shape as a means to study movements from behavioural and expressive perspectives. Application of the concepts of quality, or “inner attitudes towards” movement, are used in the analysis of Effort. 6 Thus among Laban components, Effort and Shape were the most relevant for our specific study.

The members of our research team, in order to communicate, needed to become familiar with each other’s language, e.g., the terms “High Level-Low Level” for the engineers referred to qualities of information, but to the cho- reographer and actor referred to placement in space. Symbols are interna- tional in a way that words are not. Laban’s terminology and symbols become meaningful with the consciously experienced three-dimensional sculptural movements. For examples of the symbols employed in this research, please refer to our chapter 1.

In designing the movement pathways, inspiration was taken from the types of movements similar to those of the fronds in the sculpture. The goal in designing the choreographed pathways was to choose several simple arm movements that were not already strongly weighted with affect, but were as neutral as pos- sible. It is important to reinforce the fact that different factors such as culture, physique, personal history, and specific environmental circumstances influence a quality of movement. North states that “[i]t is impossible to say either that a particular movement equals a special quality or that a particular quality equals one movement pattern plus a certain shape or space characteristic.

96 LIVING ARCHITECTURE SYSTEMS GROUP WHITE PAPERS 2016

Only generalizations can be made, because a movement assessment is made by the meticulous study of observed movement patterns of each individual.”^7

Based on the study of gestures and accompanying experimentation, three simple pathways were chosen; each was also reversed, making a total of six pathways without strong affective associations. The more limited the prescribed pathway the higher the possibility of measuring subtle significant differences between the emotions. For each of the six paths, a professional actor was asked to act each of Ekman’s original Six Basic Emotions: anger, happiness, disgust, sadness, surprise and fear.^8 Prinz acknowledges that they have become the most widely accepted candidates for basic emotions, both psychologically and biologically.^9 In LMA, the word “intent” is used to describe part of the preparation stage of movement and Hackney states “it is at this crucial point that the brain is formulating (even in a split second) the motor plan which will eventually be realized in action.”^10 As noted in Psychology of Dance , the more vivid, realistic and detailed the image is, the more the senses, thoughts and emotions are involved.^11 The actor relied on her rigorous train- ing in the use of memory and imagination to freshly create and express the emotion aroused internally.

With five tries for each emotion, we captured 180 movement sequences (6 paths, 6 emotions, 5 trials) for each of three data sets. The actor filled out a questionnaire rating her feeling of success at embodying the specific emotion for each try. The training of the actor, the number of tries, and the actor’s questionnaire, were attempts at providing high quality motion cap- ture examples of the six emotions.

A coding sheet was devised for the Laban Certified Movement Analyst (CMA) to use while watching the video of each movement. The first LMA factor quantified was Weight Effort, which describes the sense of force of one’s movement, with the contrasting elements Strong and Light. The second LMA factor quantified was Time Effort, which describes the sense of urgency, with the contrasting elements Sudden and Sustained. The third LMA factor quantified was Space Effort, which describes the attention to surroundings, with the contrasting elements Direct and Indirect. The fourth LMA factor quantified was Flow Effort, which describes the attitude towards bodily tension and control, with the contrasting elements Bound and Free. The final LMA aspect considered was Shape Directional, which defines the pathway to connect to or from the demonstrator with their goal in space, with the two categories of Arc-like and Spoke-like.

98 LIVING ARCHITECTURE SYSTEMS GROUP WHITE PAPERS 2016

Endnotes

This paper is an example illustrated from our collaborative work, “Laban Movement Analysis and Affective Movement Generation for Robots and Other Near-Living Creatures.” 1

%XUWRQ6DUDK-DQHDQG$OL$NEDU6DPDGDQL5RERUEHW'DQD.XOLþ´/DEDQ0RYHPHQW$QDO\VLV and Affective Movement Generation for Robots and Other Near-Living Creatures.” Dance Notations and Robot Motion, edited by Jean-Paul Laumond and Naoko Abe, Springer International, 2016, pp. 25-48. .DUJ0LFKHOOHDQG$6DPDGDQL5RUEHW..XHKQOHQ]-+RH\'.XOLþ´%RG\0RYHPHQWVIRU Affective Expression: a Survey of Automatic Recognition and Generation.” IEEE Transactions on Affective Computing 4(4), 2013, pp. 341–359.

  1. Laban, Rudolf, revised and enlarged by Lisa Ullmann. The Mastery of Movement, 3rd ed., PLAYS Inc., Boston, 1972.
  2. Bloom, Katya. “Interrelationships Between Movement Analysis and Psychoanalysis: a Qualitative Research Project.” Journal of Laban Movement Studies, 1(1), 2009 Spring, pp. 33–43.
  3. Kagan, Betsy. “What is spatial tension?” Discussion no. 28, Dance Notation Bureau Theory Bulletin Board, http://dnbtheorybb.blogspot.ca/2010/01/ what-is-spatial-tension.html, 2007.
  4. Bartenieff, Irmgard with Dori Lewis. Body movement: coping with the environment, Gordon and Breach Science Publishers, New York, 1980.
  5. North, Marion. Personality Assessment Through Movement, Macdonald and Evans Ltd., Estover, Plymouth, 1972.
  6. Ekman, Paul. “Are there basic emotions?” Psychology Review, 99(3), 1992, pp. 550–553.
  7. Prinz, Jesse. “Which Emotions Are Basic?” Emotion, Evolution, and Rationality, edited by D. Evans and P. Cruse, Oxford University Press, 2004, pp.69-88.
  8. Hackney, Peggy. Making Connections: Total Body Integration Through Bartenieff Fundamentals, Gordon and Breach, Amsterdam, 1988.
  9. Taylor, Jim and Ceci. Taylor. Psychology of Dance, Human Kinetics, Champaign, 1995.
  10. Blakeslee, Sandra and Matthew Blakeslee. The Body Has a Mind of Its Own, Random House, New York,

Sarah Jane Burton is a Laban Certified Movement Analyst, Ms. Burton has degrees in Movement and Dance from Butler University, IN, and Wesleyan University, CT. As a researcher she has collaborated with com- puter engineers and has co-written the chapter, “Laban Movement Analysis and Affective Movement Generation for Robots and Other Near-Living Creatures” in Dance Notations and Robot Motion published in 2016 by Springer, as well as given invited talks on the subject in the U.K. and France. Her teaching career includes positions in George Brown’s Theatre Dept., the University of Toronto’s Faculty of Music, Sheridan College’s Music Theatre Dept. and a professorship in Sheridan’s co-program in Theatre and Drama Studies with the University of Toronto Mississauga. Ms. Burton received extensive training and performed professionally in dance and theatre in New York, Chicago, Toronto, Ghana, and France. She continues to direct and choreograph professionally, including coaching actors in a television series how to simulate movement in zero gravity. Ms. Burton currently researches the enhancement of expressive movement qualities in people with Parkinson’s.

BURTON THE VALUE AND USE OF LABAN MOVEMENT ANALYSIS