The continuous development of graphics hardware is
contributing to the creation of 3D virtual worlds with
high level of detail, from models of large urban areas, to
complete infrastructures, such as residential buildings,
stadiums, industrial settings or archaeological sites, to
name just a few. Adding virtual humans or avatars adds
an extra touch to the visualization providing an enhanced
perception of the spaces, namely adding a sense of scale,
and enabling simulations of crowds. Path planning for
crowds in a meaningful way is still an open research
field, particularly when it involves an unknown polygonal
3D world. Extracting the potential paths for navigation in
a non automated fashion is no longer a feasible option
due to the dimension and complexity of the virtual
environments available nowadays. This implies that we
must be able to automatically extract information from
the geometry of the unknown virtual world to define
potential paths, determine accessibilities, and prepare a
navigation structure for real time path planning and path
finding. A new image based method is proposed that
deals with arbitrarily a priori unknown complex virtual
worlds, namely those consisting of multilevel passages
(e.g. over and below a bridge). The algorithm is capable
of extracting all the information required for the actual
navigation of avatars, creating a hierarchical data
structure to help both high level path planning and low
level path finding decisions. The algorithm is image
based, hence it is tessellation independent, i.e. the
algorithm does not rely on the underlying polygonal
structure of the 3D world. Therefore, the number of
polygons does not have a significant impact on the
performance, and the topology has no weight on the
results.Fundação para a Ciência e a Tecnologi