Abstract
We have empirically discovered that the space of human actions has a linguistic framework. This is a sensorimotor space consisting of the evolution of the joint angles of the human body in movement. The space of human activity has its own phonemes, morphemes, and sentences formed by syntax. This has implications for the grounding of concrete motion concepts. We present a Human Activity Language (HAL) for symbolic non-arbitrary representation of visual and motor information. In phonology, we define basic atomic segments that are used to compose human activity. We introduce the concept of a kinetological system and propose basic properties for such a system: compactness, view-invariance, reproducibility, and reconstructivity. In morphology, we extend sequential language learning to incorporate associative learning with our parallel learning approach. Parallel learning solves the problem of overgeneralization and is effective in identifying the kinetemes and active joints in a particular action. In syntax, we suggest four lexical categories for our Human Activity Language (noun, verb, adjective, adverb). These categories are combined into sentences through specific syntax for human movement.
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References
Bailey, D., Chang, N., Feldman, J., Narayanan, S.: Extending Embodied lexical development. In: 20th Annual Meeting of the Cognitive Science Society (1997)
Fod, A., Mataric, M., Jenkins, O.: Automated derivation of primitives for movement classification. Autonomous Robots 12(1), 39–54 (2002)
Gallese, V., Fadiga, L., Fogassi, L., Rizzolatti, G.: Action recognition in the premotor cortex. Brain 119(2), 593–609 (1996)
Glenberg, A., Kaschak, M.: Grounding language in action. Psychonomic Bulletin & Review 9(3), 558–565 (2002)
Kahol, K., Tripathi, P., Panchanathan, S.: Automated gesture segmentation from dance sequences. In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 883–888 (2004)
Nakazawa, A., Nakaoka, S., Ikeuchi, K., Yokoi, K.: Imitating human dance motions through motion structure analysis. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2539–2544 (2002)
Nevill-Manning, C., Witten, I.: Identifying hierarchical structure in sequences: A linear-time algorithm. Journal of Artificial Intelligence Research 7, 67–82 (1997)
Nishitani, N., Schurmann, M., Amunts, K., Hari, R.: Broca’s region: from action to language. Physiology 20, 60–69 (2005)
Siskind, J.: Grounding the lexical semantics of verbs in visual perception using force dynamics and event logic. Journal of Artificial Intelligence Research 15, 31–90 (2001)
Solan, Z., Horn, D., Ruppin, E., Edelman, S.: Unsupervised learning of natural languages. Proceedings of National Academy of Sciences 102(33), 11629–11634 (2005)
Wang, T.-S., Shum, H.-Y., Xu, Y.-Q., Zheng, N.-N.: Unsupervised analysis of human gestures. In: IEEE Pacific Rim Conference on Multimedia, pp. 174–181 (2001)
Wolff, J.: Learning syntax and meanings through optimization and distributional analysis. In: Levy, Y., Schlesinger, I., Braine, M. (eds.) Categories and processes in language acquisition, pp. 179–215. Lawrence Erlbaum Associates, Inc., Hillsdale (1988)
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Guerra-Filho, G., Aloimonos, Y. (2008). Grounding Concrete Motion Concepts with a Linguistic Framework. In: Darzentas, J., Vouros, G.A., Vosinakis, S., Arnellos, A. (eds) Artificial Intelligence: Theories, Models and Applications. SETN 2008. Lecture Notes in Computer Science(), vol 5138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87881-0_1
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DOI: https://doi.org/10.1007/978-3-540-87881-0_1
Publisher Name: Springer, Berlin, Heidelberg
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