Paper Info
Title
Multi-objects association in perception of dynamical situation
Abstract
In current perception systems applied to the rebuilding of the environment for intelligent vehicles, the part reserved to object association for the tracking is increasingly significant. This allows firstly to follow the objects temporal evolution and secondly to increase the reliability of environment perception. We propose in this communication the development of a multiobjects association algorithm with ambiguity removal entering into the design of such a dynamic perception system for intelligent vehicles. This algorithm uses the belief theory and data modelling with fuzzy mathematics in order to be able to handle inaccurate as well as uncertain information due to imperfect sensors. These theories also allow the fusion of numerical as well as symbolic data. We develop in this article the problem of matching between known and perceived objects. This makes it possible to update a dynamic environment map for a vehicle. The belief theory will enable us to quantify the belief in the association of each perceived object with each known object. Conflicts can appear in the case of object appearance or disappearance, or in the case of a confused situation or bad perception. These conflicts are removed or solved using an assignment algorithm, giving a solution called the «best» and so ensuring the tracking of some objects present in our environment.
Year
Venue
Keywords
2013
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
current perception system,intelligent vehicle,belief theory,multi-objects association,known object,environment perception,dynamical situation,assignment algorithm,object appearance,dynamic perception system,bad perception,dynamic environment map
DocType
Volume
ISBN
Journal
abs/1301.6701
1-55860-614-9
Citations 
PageRank 
References 
3
0.91
3
Authors
2
Name
Order
Citations
PageRank
Dominique Gruyer148552.30
Véronique Berge-cherfaoui231.59