Conference PaperPDF Available

Recognizing Movement Qualities: Mapping LMA Effort Factors to Visualization of Movement

Authors:

Abstract and Figures

Our research explores methods for developing new models and computation for utilizing meaning in movement. We present a prototype wearable system titled EffortDetect for extracting and analyzing human movement quality data using a single accelerometer. This system applies Laban Movement Analysis (LMA), a rigorous framework for understanding and analyzing human movement, to recognize different movement qualities from acceleration input. Our machine-learning software is used to classify movement qualities as they are performed in real time. We provide an example of a real-world use of the system and identify questions for discussion in the workshop.
Content may be subject to copyright.
A preview of the PDF is not available
... Perkara ini disebabkan kebanyakan penari yang menarikan tarian Mongigol-Sumundai terdiri daripada generasi muda dan tidak menguasai ragam gerak secara menyeluruh. Menurut perspektif masyarakat Momogun-Rungus, penari wanita yang baik adalah penari yang dapat mengikut rentak pergerakan dan bijak memadankan ragam gerak penari lelaki dengan ragam gerak penari wanita seperti yang ditunjukkan dalam Jadual 2. Berdasarkan kaedah participant observation yang dijalankan oleh pengkaji ke atas ragam gerak lelaki dan wanita yang berlangsung di lapangan, pengkaji dapati bahawa secara keseluruhannya tarian Mongigol-Sumundai boleh dikodkan sebagai Dabbing Effort seperti yang ditunjukkan dalam Jadual 3. Diagram Dabbing Effort diambil daripada Laban's Eight Basic Effort dengan melihat kepada effort movement atau kualiti gerak yang dihasilkan (Subyen et al., 2013). Melalui bacaan Dabbing Effort, kita boleh melihat kepada tiga kompenen utama iaitu ruang atau arah, pengunaan tenaga, dan penggunaan tempoh (Dave, 2006). ...
Article
Full-text available
Tarian Mongigol-Sumundai merupakan tarian tradisional Momogun-Rungus yang mendiami daerah Kudat, Pitas dan sebahagian kecil di kawasan Sandakan yang terletak di bahagian pantai barat utara negeri Sabah. Tarian ini sering dipersembahkan dalam majlis keramaian seperti majlis perkahwinan, sambutan Pesta Kaamatan dan Pesta Moginakan. Fokus kajian ini adalah pada konsep persembahan tarian Mongigol-Sumundai dan ragam gerak yang digunakan dalam persembahan tarian ini. Hasil pemerhatian dan analisis mendapati bahawa tarian Mongigol-Sumundai mempunyai dua konsep persembahan dan setiap konsep persembahan ini mempunyai fungsi yang berbeza. Selain itu, pengkaji juga dapat mengenal pasti 12 ragam gerak yang selalu digunakan dalam persembahan tarian Mongigol-Sumundai dan keseluruhan ragam gerak ini akan dinilai dari segi kualiti gerak menggunakan Laban Eight Effort Movement. Kajian seumpama ini penting bagi mendalami dan memahami konsep persembahan dan ragam gerak yang terkandung dalam persembahan tarian Mongigol-Sumundai. The Mongigol-Sumundai dance is a traditional Momogun-Rungus choreography that lives in the Kudat, Pitas and Sandakan districts of the north west coast of Sabah. Often this dance is performed at weddings, Kaamatan Festival and Moginakan Festival ceremonies. The key focus of this analysis is the idea of dance performance by Mongigol-Sumundai and the diversity of movements used in this dance performance. The results of observations and studies have shown Mongolian-Sumundai dance to have two performance concepts and each concept has a different function. The researcher was also able to classify 12 moving styles that are commonly used for the Mongigol-Sumundai dance performances and the entire range of these movements can be evaluated by means of the Laban Eight Effort Movement in terms of movement efficiency. Such a research is essential for us to deepen and understand the concept of performance and the diversity of movements in the dance performance of Mongigol-Sumundai.
... Perkara ini disebabkan kebanyakan penari yang menarikan tarian Mongigol-Sumundai terdiri daripada generasi muda dan tidak menguasai ragam gerak secara menyeluruh. Menurut perspektif masyarakat Momogun-Rungus, penari wanita yang baik adalah penari yang dapat mengikut rentak pergerakan dan bijak memadankan ragam gerak penari lelaki dengan ragam gerak penari wanita seperti yang ditunjukkan dalam Jadual 2. Berdasarkan kaedah participant observation yang dijalankan oleh pengkaji ke atas ragam gerak lelaki dan wanita yang berlangsung di lapangan, pengkaji dapati bahawa secara keseluruhannya tarian Mongigol-Sumundai boleh dikodkan sebagai Dabbing Effort seperti yang ditunjukkan dalam Jadual 3. Diagram Dabbing Effort diambil daripada Laban's Eight Basic Effort dengan melihat kepada effort movement atau kualiti gerak yang dihasilkan (Subyen et al., 2013). Melalui bacaan Dabbing Effort, kita boleh melihat kepada tiga kompenen utama iaitu ruang atau arah, pengunaan tenaga, dan penggunaan tempoh (Dave, 2006). ...
Article
Full-text available
ABSTRAK Tarian Mongigol-Sumundai merupakan tarian tradisional Momogun-Rungus yang mendiami daerah Kudat, Pitas dan sebahagian kecil di kawasan Sandakan yang terletak di bahagian pantai barat utara negeri Sabah. Tarian ini sering dipersembahkan dalam majlis keramaian seperti majlis perkahwinan, sambutan Pesta Kaamatan dan Pesta Moginakan. Fokus kajian ini adalah pada konsep persembahan tarian Mongigol-Sumundai dan ragam gerak yang digunakan dalam persembahan tarian ini. Hasil pemerhatian dan analisis mendapati bahawa tarian Mongigol-Sumundai mempunyai dua konsep persembahan dan setiap konsep persembahan ini mempunyai fungsi yang berbeza. Selain itu, pengkaji juga dapat mengenal pasti 12 ragam gerak yang selalu digunakan dalam persembahan tarian Mongigol-Sumundai dan keseluruhan ragam gerak ini akan dinilai dari segi kualiti gerak menggunakan Laban Eight Effort Movement. Kajian seumpama ini penting bagi mendalami dan memahami konsep persembahan dan ragam gerak yang terkandung dalam persembahan tarian Mongigol-Sumundai. ABSTRACT The Mongigol-Sumundai dance is a traditional Momogun-Rungus choreography that lives in the Kudat, Pitas and Sandakan districts of the north west coast of Sabah. Often this dance is performed at weddings, Kaamatan Festival and Moginakan Festival ceremonies. The key focus of this analysis is the idea of dance performance by Mongigol-Sumundai and the diversity of movements used in this dance performance. The results of observations and studies have shown Mongolian-Sumundai dance to have two performance concepts and each concept has a different function. The researcher was also able to classify 12 moving styles that are commonly used for the Mongigol-Sumundai dance
... Laban Effort qualities created by dance theorist Rudolf Laban consisted of: Space (direct/indirect), Weight (strong/light), Time (sudden/sustained), and Flow (bound/free). [6] By practicing with peers in class, students gained skill and confidence. ...
Article
Full-text available
Service Learning in a sequence of Voice and Movement classes integrated experiential learning to understand accents. Students acquired skills, observed clients in Service Learning placements, reflected on best practices, and wrote about and portrayed characteristics of local characters in original monologues. Service Learning improved verbal and nonverbal communication in community.
Article
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).
Article
Full-text available
Humans use gestures in most communicative acts. How are these gestures initiated and performed? What kinds of communicative roles do they play and what kinds of meanings do they convey? How do listeners extract and understand these meanings? Will it be possible to build computerized communicating agents that can extract and understand the meanings and accordingly simulate and display expressive gestures on the computer in such a way that they can be effective conversational partners? All these questions are easy to ask, but far more difficult to answer. In this thesis we try to address these questions regarding the synthesis and acquisition of communicative gestures. Our approach to gesture is based on the principles of movement observation science, specifically Laban Movement Analysis (LMA) and its Effort and Shape components. LMA, developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Its Effort and Shape component provide us with a comprehensive and valuable set of parameters to characterize gesture formation. The computational model (the EMOTE system) we have built offers power and flexibility to procedurally synthesize gestures based on predefined key pose and time information plus Effort and Shape qualities. To provide real quantitative foundations for a complete communicative gesture model, we have built a computational framework where the observable characteristics of gestures - not only key pose and timing but also the underlying motion qualitites - can be extracted from live performance, either in 3D motion capture data or in 2D video data, and correlated with observations validated by LMA notators. Experiments of this sort have not been conducted before and should be of interest not only to the computer animation and computer vision community but would be a powerful and valuable methodological tool for creating personalized, communicating agents.
Article
Full-text available
We present the implementation of computational Laban Movement Analysis (LMA) for human-machine interaction using Bayesian reasoning. The research field of computational human movement analysis is lacking a general underlying modelling language, i.e., how to map the features into symbols. With such a semantic descriptor, the recognition problem can be posed as a problem to recognise a sequence of symbols taken from an alphabet consisting of motion-entities. LMA has been proven successful in areas where humans are observing other humans’ movements. LMA provides a model for observation and description and a notational system (Labanotation). To implement LMA in a computer, we have chosen a Bayesian approach. The framework allows us to model the process, learn the dependencies between features and symbols and to perform online classification using LMA-labels. We have chosen the application ‘social robots’ to demonstrate the feasibility of our solution.
Conference Paper
Full-text available
Human movement analysis through vision sensing systems is an important subject regarding Human-Robot interaction. This is a growing area of research, with wide range of applications fields. The ability to recognize human actions using passive sensing modalities, is a decisive factor for machine interaction. In mobile platforms, image processing is regarded as a problem, due to constant changes. We propose an approach, based on Horopter technique, to extract Regions Of Interest (ROI) delimiting human contours. This fact will allow tracking algorithms to provide faster and accurate responses to human feature extraction. The key features are head and both hand positions, that will be tracked within image context. Posterior to feature acquisition, they will be contextualized within a technique, Laban Movement Analysis (LMA) and will be used to provide sets of classifiers. The implementation of the LMA technique will be based on Bayesian Networks. We will use these Bayesian classifiers to label/classify human emotion within the context of expressive movements. Compared to full image tracking, results improved with the implemented approach, the horopter and consequently so did classification results.
Conference Paper
Full-text available
Interaction with mobile devices that are intended for everyday use is challenging since such systems are continuously optimized towards small outlines. Watches are a particularly critical as display size, processing capabilities, and weight are tightly constraint. This work presents a watch device with an integrated gesture recognition interface. We report the resource-optimized implementation of our algorithmic solution on the watch and demonstrate that the recognition approach is feasible for such constraint devoices. The system is wearable during everyday activities and was evaluated with eight users to complete questionnaires through intuitive one-hand movements. We developed a procedure to spot and classify input gestures from continuous acceleration data acquired by the watch. The recognition procedure is based on hidden Markov models (HMM) and was fully implemented on a watch. The algorithm achieved an average recall of 79% at 93% precision in recognizing the relevant gestures. The watch implementation of continuous gesture spotting showed a delay below 3 ms for feature computation, Viterbi path processing, and final classification at less than 4 KB memory usage.
Article
Full-text available
This paper provides a framework for recording, analyzing and modeling of 3 dimensional emotional movements for embodied game applications. To foster embodied interaction, we need interfaces that can develop a complex, meaningful understanding of intention—both kinesthetic and emotional—as it emerges through natural human movement. The movements are emulated on robots or other devices with sensory-motor features as a part of games that aim improving the social interaction skills of children. The design of an example game platform that is used for training of children with autism is described since the type of the emotional behaviors depends on the embodiment of the robot and the context of the game. The results show that quantitative movement parameters can be matched to emotional state of the embodied agent (human or robot) using the Laban movement analysis. Emotional movements that were emulated on robots using this prin-ciple were tested with children in the age group 7–9. The tests show reliable recognition on most of the behaviors.
Article
Full-text available
Characteristics of physical activity are indicative of one’s mobility level, latent chronic diseases and aging process. Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess physical activity. This paper reviews the development of wearable accelerometry-based motion detectors. The principle of accelerometry measurement, sensor properties and sensor placements are first introduced. Various research using accelerometry-based wearable motion detectors for physical activity monitoring and assessment, including posture and movement classification, estimation of energy expenditure, fall detection and balance control evaluation, are also reviewed. Finally this paper reviews and compares existing commercial products to provide a comprehensive outlook of current development status and possible emerging technologies.
Article
Full-text available
Humans use gestures in most communicative acts. How are these gestures initiated and performed? What kinds of communicative roles do they play and what kinds of meanings do they convey? How do listeners extract and understand these meanings? Will it be possible to build computerized communicating agents that can extract and understand the meanings and accordingly simulate and display expressive gestures on the computer in such a way that they can be effective conversational partners? All these questions are easy to ask, but far more difficult to answer. In the thesis we try to address these questions regarding the synthesis and acquisition of communicative gestures. Our approach to gesture is based on the principles of movement observation science, specifically Laban Movement Analysis (LMA) and its Effort and Shape components. LMA, developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Its Effort and Shape component provide us with a comprehensive and valuable set of parameters to characterize gesture formation. The computational model (the EMOTE system) we have built offers power and flexibility to procedurally synthesize gestures based on predefined key pose and time information plus Effort and Shape qualities. To provide real quantitative foundations for a complete communicative gesture model, we have built a computational framework where the observable characteristics of gestures-not only key pose and timing but also the underlying motion qualities-can be extracted from live performance, either in 3D motion capture data or in 2D video data, and correlated with observations validated by LMA notators. Experiments of this sort have not been conducted before and should be of interest not only to the computer animation and computer vision community but would be a powerful and valuable methodological tool for creating personalized, communicating agents.
Article
With rigorous attention to both natural history and phenomenological accounts of kinetic phenomena, particularly the phenomenon of self-movement, this interdisciplinary book brings to the fore the long-neglected topic of animate form, and with it a long-neglected inquiry into the significance of animation. It addresses foundational and methodological issues at length. Its detailed and extensive examinations and analyses of movement range from Aristotle's recognition of motion as THE principle of nature to a critique of the common notion of movement as change of position, from critiques of present-day materialists' trivializations of movement as mere output to kinesthetically tethered accounts of the qualia of movement, from expositions of an evolutionary semantics and of the tactile-kinesthetic body as the generative source of corporeal concepts to expositions of thinking in movement and of the pan-human phenomenon of learning to move oneself. The book lays out fundamental epistemological and metaphysical dimensions of animate life.
Article
Activate and Motivate The Body Architecture Carving Shapes in Space Inner Impulse to Move Rhythm and Phrasing Affinities of Body, Space and Effort Tensions and Countertensions Group Interaction Dance Therapy Additional Applications: (a) Animals, Territory and Labananalysis (b) Functional Rehabilitation (c) Two Musicians (d) Martial Arts - Kendo (e) Dance (f) Walking Epilogue Appendices Barentieff Fundamental Exercises
Article
This paper presents a neural computing model that can automatically extract motion qualities from live performance. The motion qualities are in terms of laban movement analysis (LMA) Effort factors. The model inputs both 3D motion capture and 2D video projections. The output is a classification of motion qualities that are detected in the input. The neural nets are trained with professional LMA notators to ensure valid analysis and have achieved an accuracy of about 90% in motion quality recognition. The combination of this system with the EMOTE motion synthesis system provides a capability for automating both observation and analysis processes, to produce natural gestures for embodied communicative agents.