Full text: Close-range imaging, long-range vision

  
5. Experimental results 
In the static case, we have obtained very fast and accurate 
results which are independent of the image complexity. Results 
obtained for mobile case are coarser than for the static case, but 
they allow us a real-time discrimination between camera motion 
and motion of agents in the scene, and to extract kinematic 
characteristics of rigid motions (translations and rotations) of 
the center of segmented regions. Next step, would be to obtain a 
more precise information about the kinematic behaviour of 
boundaries to have an estimation of time-of-impact and prevent 
collisions. 
6. Conclusions and future developments 
Relative to the image analysis, the spent time to process the 
sample extracted from a video sequence is considerably shorter 
than the geometric mise-in-correspondence for conventional 
approaches based on the extraction and grouping of 
minisegments. Furthermore, our real-time analysis is 
independent of the complexity of the scene and the movements 
appearing at the image. The optimal properties of Delaunay 
decompositions are transferred to the color space and provide a 
self-organizing pattern whose parameteres can be selected by 
user. By using the propagation mechanism with so many centers 
(Voronoi sites) as much as winner colors, it is possible to 
generate an easily updatable dynamic segmentation. In the next 
future, we hope to prove that such dynamic segmentation is 
optimal w.r.t anisotropic diffusion. Some another open 
questions concern to the computational management of dynamic 
3D graphs linked to Delaunay simplicial decompositions in 
order to obtain a real-time segmentation for mobile complex 
scenes without extracting directly boundaries as in the classical 
case. 
Our results relative to the tracking are not enough satisfactory, 
and it would be desirable to extract some kinematic 
characteristics about mobile data. The analogy with Kohonen's 
Self-Organized Maps for tessellation and learning is purely 
formal, and we intend to develop it to improve coarse 
localization and tracking mobile articulated objects, s.t. the 
human hand. 
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