A Dynamic Bayesian Approach to Computational Laban Shape Quality Analysis

Table 1

Probabilistic constraints of subindicator states given the dominant Shape quality for specifying 𝑃₀(𝑅^𝑖_𝑡∣𝐿_𝑡).

Feature	𝐿𝑡=𝑅𝑖	𝐿𝑡=𝑆𝑖	𝐿𝑡=𝐴𝑑
𝑅^1𝑡,𝑅^2𝑡,𝑅^3𝑡	𝑝^−≪1,𝑝^+≫𝑝^−	𝑝^+≪1,𝑝^−≫𝑝^+	𝑝^−≪1,𝑝^+≪1
𝑅^4𝑡	𝑝^−≪1,𝑝^+≪1	𝑝^+≪1,𝑝^−≪1	𝑝^−≪1,𝑝^+≫𝑝^−
𝑅^5𝑡	𝑝^−≪1,𝑝^+≪1	𝑝^+≪1,𝑝^−≪1	𝑝^−≪1,𝑝^+≪1
Feature	𝐿𝑡=𝑅𝑒	𝐿𝑡=𝑆𝑝	𝐿𝑡=𝐸𝑛
𝑅^1𝑡,𝑅^2𝑡,𝑅^3𝑡	𝑝^−≪1,𝑝^+≪1	𝑝^−≪1,𝑝^+≪1	𝑝^−≪1,𝑝^+≪1
𝑅^4𝑡	𝑝^+≪1,𝑝^−≫𝑝^+	𝑝^−≪1,𝑝^+≪1	𝑝^−≪1,𝑝^+≪1
𝑅^5𝑡	𝑝^+≪1,𝑝^−≪1	𝑝^−≪1,𝑝^+≫𝑝^−	𝑝^+≪1,𝑝^−≫𝑝^+
Feature	𝐿𝑡=𝑁𝑒
𝑅^1𝑡,𝑅^2𝑡,𝑅^3𝑡	𝑝^−≪1,𝑝^+≪1
𝑅^4𝑡	𝑝^−≪1,𝑝^+≪1
𝑅^5𝑡	𝑝^−≪1,𝑝^+≪1