@inproceedings{beetz_towards_2009,
 author = {M Beetz and J Bandouch and D Jain and M Tenorth},
 title = {Towards Automated Models of Activities of Daily Life},
 booktitle = {First International Symposium on Quality of Life Technology – Intelligent
	Systems for Better Living},
 year = {2009},
 address = {Pittsburgh, Pennsylvania {USA}},
 abstract = {We propose automated probabilistic models of everyday activities ({AM-EvA)}
	as a novel technical means for the perception, interpretation, and
	analysis of everyday manipulation tasks and activities of daily life.
	{AM-EvAs} are based on action-related concepts in everyday activities
	such as action-related places (the place where cups are taken from
	the cupboard), capabilities (the objects that can be picked up single-handedly),
	etc. These concepts are probabilistically derived from a set of previous
	activities that are fully and automatically observed by computer
	vision and additional sensor systems. {AM-EvA} models enable robots
	and technical systems to analyze activities in the complete situation
	and activity context. They render the classification and the assessment
	of actions and situations objective and can justify the probabilistic
	interpretation with respect to the activities the concepts have been
	learned from. In this paper, we describe the current state of implementation
	of the system that realizes this idea of automated models of everyday
	activities and show example results from the observation and analysis
	of table setting episodes.},
}

@inproceedings{beetz_towards_2009,
 author = {M Beetz and J Bandouch and D Jain and M Tenorth},
 title = {Towards Automated Models of Activities of Daily Life},
 booktitle = {First International Symposium on Quality of Life Technology – Intelligent
	Systems for Better Living},
 year = {2009},
 address = {Pittsburgh, Pennsylvania {USA}},
 abstract = {We propose automated probabilistic models of everyday activities ({AM-EvA)}
	as a novel technical means for the perception, interpretation, and
	analysis of everyday manipulation tasks and activities of daily life.
	{AM-EvAs} are based on action-related concepts in everyday activities
	such as action-related places (the place where cups are taken from
	the cupboard), capabilities (the objects that can be picked up single-handedly),
	etc. These concepts are probabilistically derived from a set of previous
	activities that are fully and automatically observed by computer
	vision and additional sensor systems. {AM-EvA} models enable robots
	and technical systems to analyze activities in the complete situation
	and activity context. They render the classification and the assessment
	of actions and situations objective and can justify the probabilistic
	interpretation with respect to the activities the concepts have been
	learned from. In this paper, we describe the current state of implementation
	of the system that realizes this idea of automated models of everyday
	activities and show example results from the observation and analysis
	of table setting episodes.},
}