Quantitative and qualitative properties of selected studies on activity and intention recognition.

“▪” = feature included in study.“□” = feature not included.“x†” = value/property x not explicitly stated in study description.“–” = value unknown.“◊” = property not meaningful considering target of study.Method codes: L: logic-based (DL = description logic, P = combined with possibility theory). B: using some variant of sequential Bayesian filtering (exact: H = HMM or extension, D = other DBN, Pl = transformation into a planning problem, P = partially observable Markov decision process; approximate: PF = particle filter, RP = Rao-Blackwellized particle filter, MF = marginal filter). N = Non-sequential Bayesian inference (MH = Metropolis-Hastings, BN = unrolled Bayes Net). O = other exact method (G = some kind of grammar, ML = Markov Logic net). Scenario codes: K = kitchen task, A = other activities of daily living, O = office, M = miscellaneous other scenario.We consider the first five studies as CSSM-like approaches.Quantitative and qualitative properties of selected studies on activity and intention recognition.