Abstract
We present WalkNet, an interactive agent walking movement controller based on neural networks. WalkNet supports controlling the agent’s walking movements with high-level factors that are semantically meaningful, providing an interface between the agent and its movements in such a way that the characteristics of the movements can be directly determined by the internal state of the agent. The controlling factors are defined across the dimensions of planning, affect expression, and personal movement signature. WalkNet employs Factored, Conditional Restricted Boltzmann Machines to learn and generate movements. We train the model on a corpus of motion capture data that contains movements from multiple human subjects, multiple affect expressions, and multiple walking trajectories. The generation process is real-time and is not memory intensive. WalkNet can be used both in interactive scenarios in which it is controlled by a human user and in scenarios in which it is driven by another AI component.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Alemi, O., Li, W., Pasquier, P.: Affect-expressive movement generation with factored conditional restricted boltzmann machines. In: Proceedings of the International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 442–448 (2015)
Brand, M., Hertzmann, A.: Style machines. In: Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques, pp. 183–192. ACM Press/Addison-Wesley Publishing Co. (2000)
Crnkovic-Friis, L., Crnkovic-Friis, L.: Generative choreography using deep learning. In: Proceedings of the 7th International Conference on Computational Creativity (2016)
Grassia, F.S.: Practical Parameterization of Rotations Using the Exponential Map. Journal of Graphics Tools 3(3), 29–48 (1998)
Heck, R., Gleicher, M.: Parametric motion graphs. In: Proceedings of the 29th Representation Learning Workshop, International Conference on Machine Learning, pp. 129–136. ACM Press (2007)
Herzog, D., Krueger, V., Grest, D.: Parametric hidden markov models for recognition and synthesis of movements. In: Proceedings of the British Machine Vision Conference, pp. 163–172 (2008)
Holden, D., Saito, J., Komura, T.: A Deep Learning Framework for Character Motion Synthesis and Editing. ACM Transactions on Graphics (TOG) 35(4), 138–11 (2016)
Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. In: SIGGRAPH 2002: Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques, pp. 473–482. ACM Press (2002)
Plutchik, R., Conte, H.R.: Circumplex Models of Personality and Emotions. American Psychological Association (1997)
Samadani, A.A., Kubica, E., Gorbet, R., Kulić, D.: Perception and Generation of Affective Hand Movements. International Journal of Social Robotics 5(1), 35–51 (2013)
Taubert, N., Endres, D., Christensen, A., Giese, M.A.: Shaking hands in latent space - modeling emotional interactions with gaussian process latent variable models. In: Bach, J., Edelkamp, S. (eds.) KI 2011. LNCS, vol. 7006, pp. 330–334. Springer, Heidelberg (2011). doi:10.1007/978-3-642-24455-1_32
Taylor, G.W., Hinton, G.E.: Factored conditional restricted boltzmann machines for modeling motion style. In: Proceedings of the 26th Annual International Conference on Machine Learning (2009)
Tilmanne, J., d’Alessandro, N., Astrinaki, M., Ravet, T.: Exploration of a stylistic motion space through realtime synthesis. In: Proceedings of the 9th International Conference on Computer Vision Theory and Applications, pp. 1–7 (2014)
Wang, J.M., Fleet, D.J., Hertzmann, A.: Multifactor gaussian process models for style-content separation. In: Proceedings of the 24th International Conference on Machine Learning, pp. 975–982. ACM Press (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Alemi, O., Pasquier, P. (2017). WalkNet: A Neural-Network-Based Interactive Walking Controller. In: Beskow, J., Peters, C., Castellano, G., O'Sullivan, C., Leite, I., Kopp, S. (eds) Intelligent Virtual Agents. IVA 2017. Lecture Notes in Computer Science(), vol 10498. Springer, Cham. https://doi.org/10.1007/978-3-319-67401-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-67401-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67400-1
Online ISBN: 978-3-319-67401-8
eBook Packages: Computer ScienceComputer Science (R0)