![](bg8.png)
Our results show that learning based visualization
is a promising approach, even if the technique learned
by our current algorithm is not always the best in
our experiments. We have presented only early re-
sults and there is much scope for further study in
this direction. There is a need for to devise a theo-
retical framework for determining useful parameters
to learn. Algorithmic work is also required to al-
low faster computation of view-dependent training re-
sults for interactive manipulation. Also, other render-
ing techniques like specular lighting and cast shadows
could be added to the learning set. A more efficient
training set generation would also be useful in making
the technique user friendly.
ACKNOWLEDGEMENTS
We thank the Department of Science and Technology
for funding this research and Lissy Verma for imple-
menting several basis rendering techniques. We also
thank the reviewers for helping improve the presenta-
tion of the paper.
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