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Grounding Concrete Motion Concepts with a Linguistic Framework

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Artificial Intelligence: Theories, Models and Applications (SETN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5138))

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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

  1. Bailey, D., Chang, N., Feldman, J., Narayanan, S.: Extending Embodied lexical development. In: 20th Annual Meeting of the Cognitive Science Society (1997)

    Google Scholar 

  2. Fod, A., Mataric, M., Jenkins, O.: Automated derivation of primitives for movement classification. Autonomous Robots 12(1), 39–54 (2002)

    Article  MATH  Google Scholar 

  3. Gallese, V., Fadiga, L., Fogassi, L., Rizzolatti, G.: Action recognition in the premotor cortex. Brain 119(2), 593–609 (1996)

    Article  Google Scholar 

  4. Glenberg, A., Kaschak, M.: Grounding language in action. Psychonomic Bulletin & Review 9(3), 558–565 (2002)

    Google Scholar 

  5. 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)

    Google Scholar 

  6. 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)

    Google Scholar 

  7. Nevill-Manning, C., Witten, I.: Identifying hierarchical structure in sequences: A linear-time algorithm. Journal of Artificial Intelligence Research 7, 67–82 (1997)

    MATH  Google Scholar 

  8. Nishitani, N., Schurmann, M., Amunts, K., Hari, R.: Broca’s region: from action to language. Physiology 20, 60–69 (2005)

    Article  Google Scholar 

  9. 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)

    MATH  Google Scholar 

  10. Solan, Z., Horn, D., Ruppin, E., Edelman, S.: Unsupervised learning of natural languages. Proceedings of National Academy of Sciences 102(33), 11629–11634 (2005)

    Article  Google Scholar 

  11. 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)

    Google Scholar 

  12. 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)

    Google Scholar 

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John Darzentas George A. Vouros Spyros Vosinakis Argyris Arnellos

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© 2008 Springer-Verlag Berlin Heidelberg

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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

  • Print ISBN: 978-3-540-87880-3

  • Online ISBN: 978-3-540-87881-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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