CFP : Int WS Situational Awareness - France - 22FEB2010
Vision List Digest:
Article 11,
Volume 29, Issue 2
From: Kinh Tieu
Post-Followup: submission@VISLIST.com
Call for Papers
International Workshop on Situational Awareness for
Autonomous and Mobile Platforms (SAAM 2010)
In conjunction with VISIGRAPP, May, 2010 - Angers, France
http://www.visigrapp.org/SAAM.htm
IMPORTANT DATES
Regular Paper Submission: January 12, 2010
Authors Notification: February 09, 2010
Final Paper Submission and Registration: February 22, 2010
CHAIRS
David Demirdjian, Vecna Robotics, USA
Kinh Tieu, Mitsubishi Electric Research Laboratories, USA
SCOPE
The SAAM workshop solicits papers on new research directions, works-in-
progress, and critical surveys of prior work in all areas pertaining to
situational awareness for autonomous and mobile platforms.
To navigate and operate successfully, autonomous systems need to build a
consistent spatial and temporal representation of the world, including
for instance, the environment geometry and properties, as well as human
presence, intent and activity. Humans are able to build such
representations from observations and experience, and therefore are
situationally aware.
How to build and use such situational awareness (SA) representations is
still a fundamental research area, which this workshop seeks to address.
In particular the workshop aims at gathering papers focused on SA
modeling techniques, e.g., how to convert raw, low-level, sensing
information to representations that are useful for autonomous system
tasks. As vision is the most commonly used sensing modality, the
workshop is mainly interested in systems using visual sensors (video
cameras, 3D sensors, multi-spectral sensors). However, systems including
additional modalities such as audio and haptic sensing are welcome.
TOPICS
This workshop encompasses a broad range of research areas. Therefore,
the potential topics for discussion at this workshop are also wide-
ranging:
* New and innovative computer vision algorithms for mobile
platforms (SLAM, obstacle detection, object recognition)
* Design methodologies for computer vision and robotic systems
* Reasoning, goal, specification, perception-action loops
* Use of task context, context awareness, knowledge representations
* Multimodal fusion
* Ontology-based representations
* Model-based (geometric) representations
* Data-driven (image-based) representations
* Human-Machine Interaction
* Ubiquitous computing
* Calibration and auto-calibration
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