Abstract
We propose a linguistic approach to model human activity. This approach is able to address several problems related to action interpretation in a single framework. The Human Activity Language (HAL) consists of kinetology, morphology, and syntax. Kinetology, the phonology of human movement, finds basic primitives for human motion (segmentation) and associates them with symbols (symbolization). The input is measurements of human movement in 3D (signals), as for example produced by motion capture systems. This way, kinetology provides a non-arbitrary grounded symbolic representation for human movement that allows synthesis, analysis, and symbolic manipulation. The morphology of a human action is related to the inference of essential parts of the movement (morpho-kinetology) and its structure (morpho-syntax). In order to learn the morphemes and their structure, we present a grammatical inference methodology and introduce a parallel learning algorithm to induce a grammar system representing a single action. In practice, morphology is concerned with the construction of a vocabulary of actions or a praxicon. The syntax of human activities involves the construction of sentences using action morphemes. A sentence may range from a single action morpheme (nuclear syntax) to a sequence of sets of morphemes. A single morpheme is decomposed into analogs of lexical categories: nouns, adjectives, verbs, and adverbs. The sets [[lt]]of morphemes represent simultaneous actions (parallel syntax) and a sequence of movements is related to the concatenation of activities (sequential syntax). Nuclear syntax, especially adverbs, is related to the motion interpolation problem, parallel syntax addresses the slicing problem, and sequential syntax is proposed as an alternative method to the transitioning problem. Consequences of the framework to recognition of Action, imitation and Cognitive Science will be discussed.