326 research outputs found
A Motion Control Scheme for Animating Expressive Arm Movements
Current methods for figure animation involve a tradeoff between the level of realism captured in the movements and the ease of generating the animations. We introduce a motion control paradigm that circumvents this tradeoff-it provides the ability to generate a wide range of natural-looking movements with minimal user labor.
Effort, which is one part of Rudolf Laban\u27s system for observing and analyzing movement, describes the qualitative aspects of movement. Our motion control paradigm simplifies the generation of expressive movements by proceduralizing these qualitative aspects to hide the non-intuitive, quantitative aspects of movement. We build a model of Effort using a set of kinematic movement parameters that defines how a figure moves between goal keypoints. Our motion control scheme provides control through Effort\u27s four dimensional system of textual descriptors, providing a level of control thus far missing from behavioral animation systems and offering novel specification and editing capabilities on top of traditional keyframing and inverse kinematics methods. Since our Effort model is inexpensive computationally, Effort-based motion control systems can work in real-time.
We demonstrate our motion control scheme by implementing EMOTE (Expressive MOTion Engine), a character animation module for expressive arm movements. EMOTE works with inverse kinematics to control the qualitative aspects of end-effector specified movements. The user specifies general movements by entering a sequence of goal positions for each hand. The user then expresses the essence of the movement by adjusting sliders for the Effort motion factors: Space, Weight, Time, and Flow. EMOTE produces a wide range of expressive movements, provides an easy-to-use interface (that is more intuitive than joint angle interpolation curves or physical parameters), features interactive editing, and real-time motion generation
Pathway to Future Symbiotic Creativity
This report presents a comprehensive view of our vision on the development
path of the human-machine symbiotic art creation. We propose a classification
of the creative system with a hierarchy of 5 classes, showing the pathway of
creativity evolving from a mimic-human artist (Turing Artists) to a Machine
artist in its own right. We begin with an overview of the limitations of the
Turing Artists then focus on the top two-level systems, Machine Artists,
emphasizing machine-human communication in art creation. In art creation, it is
necessary for machines to understand humans' mental states, including desires,
appreciation, and emotions, humans also need to understand machines' creative
capabilities and limitations. The rapid development of immersive environment
and further evolution into the new concept of metaverse enable symbiotic art
creation through unprecedented flexibility of bi-directional communication
between artists and art manifestation environments. By examining the latest
sensor and XR technologies, we illustrate the novel way for art data collection
to constitute the base of a new form of human-machine bidirectional
communication and understanding in art creation. Based on such communication
and understanding mechanisms, we propose a novel framework for building future
Machine artists, which comes with the philosophy that a human-compatible AI
system should be based on the "human-in-the-loop" principle rather than the
traditional "end-to-end" dogma. By proposing a new form of inverse
reinforcement learning model, we outline the platform design of machine
artists, demonstrate its functions and showcase some examples of technologies
we have developed. We also provide a systematic exposition of the ecosystem for
AI-based symbiotic art form and community with an economic model built on NFT
technology. Ethical issues for the development of machine artists are also
discussed
Thai dance knowledge archive framework based on Labanotation represented in 3D animation
© 2017 IEEE.Southeast Asia is one of the most rapidly growing regions in the world with natural and cultural resources. It is important to pass on the cultural knowledge to the next generation. Intangible Cultural Heritage like traditional dances, or folk dance is a valuable cultural knowledge to be maintained and passed on by transferring tacit knowledge, and even explicit knowledge such as books, or video presentations. Issues of passing on the knowledge can be the loss of knowledge from time to time by the reduction of the number of dance masters, unreliable sources, and low quality. To retrieve such valuable knowledge, there is a widely-used tool in Europe, in the United States, Asia and Southeast Asia, called 'Labanotation' which is about recording and analyzing the dance movement. This paper focuses on proposing a framework for a traditional Thai dance knowledge archive creating an ontology using knowledge engineering based on Labanotation by transferring notation scores to represent the dance in 3D Animation. The framework assists dancers, notators, knowledge engineers, software engineers to successfully communicate with each other
Interactive dance choreography assistance
Creative support for the performing arts is prevalent in many fields, however, for the art of dance, automated tools supporting creativity have been scarce. In this research, we describe ongoing research into (semi)automatic automated creative choreography support. Based on state-of-the-art and a survey among 54 choreographers we establish functionalities and requirements for a choreography assistance tool, including the semantic levels at which it should operate and communicate with the end-users. We describe a user study with a prototype tool which presents choreography alternatives using various simple strategies in three dance styles. The results show that the needs for such a tool vary based on the dance discipline. In a second user study, we investigate various methods of presenting choreography variations. Here, we evaluate four presentation methods: textual descriptions, 2D animations, 3D animations and auditory instructions in two different dance styles. The outcome of the expert survey shows that the tool is effective in communicating the variations to the experts and that they express a preference for 3D animations. Based on these results, we propose a design for an interactive dance choreography assistant tool
Designing for Ballet Classes: Identifying and Mitigating Communication Challenges Between Dancers and Teachers
Dancer-teacher communication in a ballet class can be challenging: ballet is one of the most complex forms of movements, and learning happens through multi-faceted interactions with studio tools (mirror, barre, and floor) and the teacher. We conducted an interview-based qualitative study with seven ballet teachers and six dancers followed by an open-coded analysis to explore the communication challenges that arise while teaching and learning in the ballet studio. We identified key communication issues, including adapting to multi-level dancer expertise, transmitting and realigning development goals, providing personalized corrections and feedback, maintaining the state of flow, and communicating how to properly use tools in the environment. We discuss design implications for crafting technological interventions aimed at mitigating these communication challenges
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