The Perceptual Consistency and Association of the LMA Effort Elements

Author:

Kim Hye Ji1,Neff Michael2ORCID,Lee Sung-Hee1ORCID

Affiliation:

1. Korea Advanced Institute of Science Technology, Seoul, Republic of Korea

2. University of California, Davis, CA

Abstract

Laban Movement Analysis (LMA) and its Effort element provide a conceptual framework through which we can observe, describe, and interpret the intention of movement. Effort attributes provide a link between how people move and how their movement communicates to others. It is crucial to investigate the perceptual characteristics of Effort to validate whether it can serve as an effective framework to support a wide range of applications in animation and robotics that require a system for creating or perceiving expressive variation in motion. To this end, we first constructed an Effort motion database of short video clips of five different motions: walk, sit down, pass, put, wave performed in eight ways corresponding to the extremes of the Effort elements. We then performed a perceptual evaluation to examine the perceptual consistency and perceived associations among Effort elements: Space (Indirect/Direct), Time (Sustained/Sudden), Weight (Light/Strong), and Flow (Free/Bound) that appeared in the motion stimuli. The results of the perceptual consistency evaluation indicate that although the observers do not perceive the LMA Effort element 100% as intended, true response rates of seven Effort elements are higher than false response rates except for light Effort. The perceptual consistency results showed varying tendencies by motion. The perceptual association between LMA Effort elements showed that a single LMA Effort element tends to co-occur with the elements of other factors, showing significant correlation with one or two factors (e.g., indirect and free, light and free).

Funder

National Research Foundation, Korea

Publisher

Association for Computing Machinery (ACM)

Subject

Experimental and Cognitive Psychology,General Computer Science,Theoretical Computer Science

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