A Perceptual Study of the Relationship between Posture and Gesture for Virtual Characters

Luo, Pengcheng; Neff, Michael

doi:10.1007/978-3-642-34710-8_24

Cited by 12 publications

(9 citation statements)

References 22 publications

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“…Later, Zhao and Badler [ZB05] used the EMOTE results to design a neural network for gesture animation. LMA has been successfully used in many applications of computer graphics, such as motion analysis [THB06, LN12] or motion retrieval [WOTO10, OWO12, KCT*13], all with a common denominator the attempt to extract the style of motion. The LMA concept has been also utilized to quantify the expressive content of gestures with regards to the emotion [FSH03, HMP06].…”

Section: Literature Reviewmentioning

confidence: 99%

Emotion Analysis and Classification: Understanding the Performers' Emotions Using the LMA Entities

Aristidou

Charalambous

Chrysanthou

2015

Computer Graphics Forum

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The increasing availability of large motion databases, in addition to advancements in motion synthesis, has made motion indexing and classification essential for better motion composition. However, in order to achieve good connectivity in motion graphs, it is important to understand human behaviour; human movement though is complex and difficult to completely describe. In this paper, we investigate the similarities between various emotional states with regards to the arousal and valence of the Russell's circumplex model. We use a variety of features that encode, in addition to the raw geometry, stylistic characteristics of motion based on Laban Movement Analysis (LMA). Motion capture data from acted dance performances were used for training and classification purposes. The experimental results show that the proposed features can partially extract the LMA components, providing a representative space for indexing and classification of dance movements with regards to the emotion. This work contributes to the understanding of human behaviour and actions, providing insights on how people express emotional states using their body, while the proposed features can be used as complement to the standard motion similarity, synthesis and classification methods.

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Section: Literature Reviewmentioning

confidence: 99%

Emotion Analysis and Classification: Understanding the Performers' Emotions Using the LMA Entities

Aristidou

Charalambous

Chrysanthou

2015

Computer Graphics Forum

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“…PGMs have been shown empirically to correspond with verbal expressions that are authentic, relaxed, truthful, and sincere in contexts that require decision-making (Winter et al, 1989; Moore, 2005; Lamb, 2012) 1 . They have also been replicated by computer experts who model human behaviors to guide the representation of virtual characters (Luo and Neff, 2012). …”

Section: Introductionmentioning

confidence: 99%

Predicting individual differences in decision-making process from signature movement styles: an illustrative study of leaders

Connors¹,

Rende²,

Colton³

2013

Front. Psychol.

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There has been a surge of interest in examining the utility of methods for capturing individual differences in decision-making style. We illustrate the potential offered by Movement Pattern Analysis (MPA), an observational methodology that has been used in business and by the US Department of Defense to record body movements that provide predictive insight into individual differences in decision-making motivations and actions. Twelve military officers participated in an intensive 2-h interview that permitted detailed and fine-grained observation and coding of signature movements by trained practitioners using MPA. Three months later, these subjects completed four hypothetical decision-making tasks in which the amount of information sought out before coming to a decision, as well as the time spent on the tasks, were under the partial control of the subject. A composite MPA indicator of how a person allocates decision-making actions and motivations to balance both Assertion (exertion of tangible movement effort on the environment to make something occur) and Perspective (through movements that support shaping in the body to perceive and create a suitable viewpoint for action) was highly correlated with the total number of information draws and total response time—individuals high on Assertion reached for less information and had faster response times than those high on Perspective. Discussion focuses on the utility of using movement-based observational measures to capture individual differences in decision-making style and the implications for application in applied settings geared toward investigations of experienced leaders and world statesmen where individuality rules the day.

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“…The EMOTE system (Chi et al 2000) synthesises gesture, for motion parameterisation and expression, based on the LMA effort quality; then, (Zhao and Badler 2005) used the EMOTE results to design a neural network for gesture animation. A user-centered approach for incorporating affective expressions in interactive applications based on effort, shape and emotional state was presented by (Fagerberg et al 2003), whereas (Luo and Neff 2012) studied the relationship between posture and gesture for virtual characters. Finally, (Okajima et al 2012) used a subset of LMA features for motion retrieval, while (Kapadia et al 2013) proposed a method for searching motions in large databases.…”

Section: Related Workmentioning

confidence: 99%

Motion indexing of different emotional states using LMA components

Aristidou

Chrysanthou

2013

SIGGRAPH Asia 2013 Technical Briefs

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Recently, there has been an increasing use of pre-recorded motion capture data, making motion indexing and classification essential for animating virtual characters and synthesising different actions. In this paper, we use a variety of features that encode characteristics of motion using the Body, Effort, Shape and Space components of Laban Movement Analysis (LMA), to explore the motion quality from acted dance performances. Using Principal Component Analysis (PCA), we evaluate the importance of the proposed featureswith regards to their ability to separate the performer's emotional state -indicating the weight of each feature in motion classification. PCA has been also used for dimensionality reduction, laying the foundation for the qualitative and quantitative classification of movements based on their LMA characteristics. Early results show that the proposed features provide a representative space for indexing and classification of dance movements with regards to the emotion, which can be used for synthesis and composition purposes.

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A Perceptual Study of the Relationship between Posture and Gesture for Virtual Characters

Cited by 12 publications

References 22 publications

Emotion Analysis and Classification: Understanding the Performers' Emotions Using the LMA Entities

Emotion Analysis and Classification: Understanding the Performers' Emotions Using the LMA Entities

Predicting individual differences in decision-making process from signature movement styles: an illustrative study of leaders

Motion indexing of different emotional states using LMA components

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