Name
Title | ||
|---|---|---|
Strategies for modelling human behaviour for activity recognition with precondition-effect rules |
Abstract | ||
|---|---|---|
The manner in which the human behaviour and the environment are modelled greatly influences the activity recognition performance in context-aware systems and an inappropriate choice of modelling mechanism could lead to unwanted or unexpected model behaviour. In this work we present an approach for modelling human behaviour based on precondition-effect rules, and discuss in detail different modelling strategies. As a result, the paper provides useful guidelines for modelling human behaviour for activity recognition, including best practices and pitfalls that should be avoided for one to build a successful model. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33347-7_27 | KI |
Keywords | Field | DocType |
detail different modelling strategy,successful model,unexpected model behaviour,inappropriate choice,precondition-effect rule,best practice,modelling mechanism,human behaviour,activity recognition,context-aware system,activity recognition performance | Activity recognition,Best practice,Precondition,Risk analysis (engineering),Artificial intelligence,Engineering,Causal model | Conference |
Citations | PageRank | References |
2 | 0.43 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kristina Yordanova | 1 | 70 | 15.22 |
| Frank Krüger | 2 | 53 | 10.43 |
| Thomas Kirste | 3 | 93 | 18.37 |