Grounding Concrete Motion Concepts with a Linguistic Framework

  • Authors:

  • Gutemberg Guerra-Filho;Yiannis Aloimonos

  • Affiliations:

  • Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, USA 76019;Department of Computer Science, University of Maryland, College Park, USA 20742

  • Venue:
  • SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
  • Year:
  • 2008

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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.