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General Co-Chairs
Rüdiger Dillmann
Jürgen Beyerer
Program Chairs
Tanja Schultz
Uwe D. Hanebeck
Publicity Chairs
Alex Waibel
Rudi Studer
Exhibition
Chair
Heinz Wörn
Local Chair
Fernando Puente León
Workshop and Tutorial
Chairs
Marius Zöllner
Rainer Stiefelhagen
Contact
KI 2010 - Team
ki2010@kit.edu
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Description:
Almost all technical devices and software agents surrounding humans
attempt to recognize the behavior of the user. With the embedding
of an increasing number of sensors and the spread of mobile sensor
devices, e.g., Humanoid Robots, the need for theoretically well-grounded
and systematic approaches becomes eminent.
Situation, Intention, and Action Recognition relates to the process
of inferring the user’s behavior on differing scales and scopes.
The situation, defined as a set of conditions, limits the user’s
current and future behavior. Within the scope of the prevailing
situation, the user will have various coarse intentions that manifest
in fine-grained actions, i.e., manipulations of the world. Recognizing
the user’s behavior with respect to these differing levels
of abstraction may be used for the facilitation of human-machine-interactions
or the recognition of exceptional behavior. Potential applications
range from software usability to human-robot-cooperation for household-robots.
The main challenges for the recognition tasks are the fusion of
online incoming data (e.g., video streams) with appropriate domain
knowledge, e.g., relational spatio-temporal information (i.e., object
relations, human motion models or ontologies). The inference is
most often based on uncertain and hardly sufficient data (e.g.,
human action recognition based on video signals) increasing the
need for appropriate models of the human and the world. The models
necessary for non-trivial tasks entail complex hierarchical models,
spanning atomic actions to multilevel action sequences. Finally,
for many realistic scenarios, the situation can only be assessed
when taking the multi-agent context into account, i.e., the relation
of the human/user surrounded by other humans/users as well as robots.
Contributions are invited but not
limited to the following research fields and applications:
- Representations of user/human behavior
- Recognition of Situation
- Recognition of Intention
- Recognition of Action
- Machine learning for probabilistic inference
- Modeling and monitoring (multiple) agents
- User Modeling and its Applications
- Behavior Recognition for Human-machine-interaction
- Action Recognition for Programming-by-Demonstration
and Imitation Learning
Submission Guidelines:
Submitted papers, which have to be in English, should regularly
not exceed 8 pages in Springer LNCS style, two additional pages
will be permitted for an extra charge. Conference submission is
electronic, in pdf format. The paper will be treated as a regular
contribution to the conference, i.e., will be part of the regular
review process and will be published as part of conference proceedings
in the Springer Lecture Notes in AI (LNAI) series. At least one
author per accepted paper must register for the conference and present
the contribution. Papers have to be submitted before 16 April 2010
and should be marked as “special session papers” during
submission.
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