Results Publications

Computation of the distribution of light

The distribution of light inside the scene (and inside plants) is computed using a hierarchical radiosity algorithm based on instanciation. Indeed, to be able to cope with the large geometric complexity of plant models, it has been essential to develop a technique which memory cost is sub-linear in terms of the number of polygons in the scene.

Due to the high self similarity that exists in plant models, it is possible to represent a whole plant as a collection of instances of a single part of it. This representation is only an approximation because (to the difference of Fractals) self-similarity in plants is not exact; however is exists at multiple scales (branches, leaves, whole plants, etc) and it is thus theoretically possible to expand a plant using only a few basic elements. On the image below, we show an example of such a representation:

The two images below show the difference between our multi-level instanciation method and a classical hierarchical radiosity method with clustering. It appears clearly that our methos uses only a few memory as compared to the other one and runs much faster.

Classical HR with clustering.
1 hour 57 mn, 123 MB of memory
Hierarchical instanciation.
26 mn, 13MB of memory.

The image below shows lighting simulations obtained using our hierarchical instanciation method. Measurements were conducted on a Sgi Origin2000 workstation. In such cases our Instantiation algorithm prooves very usefull because the entire model can not fit in the main memory of the machine.

Marron tree.
1 hour, 80 MB of memory
10 poplar trees of various ages.
2 hours, 83 MB of memory.