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Title
New perspectives to save cultural heritage
Author
Altan, M. Orhan

CIPA 2003 XIX th International Symposium, 30 September - 04 October, 2003, Antalya, Turkey
of compressed error-image and the bytes needed to code
the projective transformation parameters.
Table 1 : Results of the frame compression algorithm
Polygon
Compr.sed
Error-image
(bytes)
Compr.sed
View B
(bytes)
Bit/
pixel
error
Bit/
pixel
view
B
Ratio
Green
625
780
0.07
0.08
1.25
Red
603
768
0.06
0.08
1.27
Yellow
586
753
0.058
0.079
1.28
It should be noted that the compression ratio is always greater
than 1, what confirms the effectiveness of implemented
compression procedure. Indeed, this means that sending to
the client both the compressed error-image and the
parameters of the projective transformation, generates a
throughput lower than the transmission of the compressed
view only. As shown in table 1, the gain is ranging between
25% and 28% in terms of bytes employed.
6. CONCLUSIONS
In this paper an innovative concept of VRML browser has
been proposed. It is aimed mainly to allow the display of
complex and large 3D models, as the ones obtained by
ground-based laser scanners, reducing the computational load
on the user-side. To this end, we developed a VRML split-
browser, which is conceptually based on a server/client
paradigm, but at the same time it keeps all the advantages of
the VRML interchange file format as suitable mean to share
3D objects along the web. The main idea on the ground of
developed architecture is the splitting of the tasks between
server and client. The former performs all the operations
requiring the most computational effort, reducing the
working load of the latter. This has been accomplished using
perspective transformations and image compression
algorithms, like LZ77. In our system the server sends to the
client only a set o parameters, defining the perspective
transformation between to 3D scenes, and a compressed
error-image, instead of the whole VRML 3D model. Then the
client uses such elements to reconstruct the view of the scene
according to the input command activated by the user on the
client’s GUI.
The proposed work is still in progress, as improvements can
be still applied, in order to further optimize the performance
of our split-browser. We are investigating the use of the
Bounding Box, view-images caching and the adoption of a
linear prediction scheme in the LZ77 algorithm. The former
would allow to compress only the portion of the whole 3D
model that is actually enclosed by the bounding box, saving
in this way the number of bytes used for the image coding.
The second solution deals with the creation of a memory
buffer on the client side, where all the views sent by the
srever are sequentially stored. In this way, if the eye-point
(user’s viewing direction) returns back on a previous visited
position, the client needs to restore the corresponding view
from the buffer: no data have to be sent from server to the
client. A further server/client throughput reduction could be
achieved by means of the linear prediction: the pixel color of
an image can be predicted on the baiss of the color of the
neighbours. Accordingly, the server would not compress the
original image but rather the so called residual-image, whose
pixels are obtained as difference of the color values of
adjacent pixels ont he source image.
ACKNOWLEDGEMENTS
This work was developed with the project “Application in the
survey, store and management of environmental and cultural
resources of GNSS/INS positioning and satellite, aerial,
terrestrial photographic and laser scanning data, transmitted
by DARC, GSM/GLOBAL STAR, INTERNET methods”,
partly financed by MURST (Italian Ministry of University
and Research) in 2002 as project of relevant National interest.
National coordinator: Giorgio Manzoni, head of the Research
unit Antonio Vettore.
REFERENCES
Carey R., Bell G, 1997. The Annotated VRML 97 Reference
Foley J., Dam A. V., Feiner S., Hughes J., 1996. Computer
Graphics: Principles and Practice. Addison-Wesley, 2 nd
edition.
Gleicher M., Projective Registration with Difference
Decomposition. URL: http/Avww. cs.wisc.edu/Graphics/
Papers/Gleicher/Califomia/track-Final.pdf
Hartley R., Zissermann A., 1999. Multiple View Geometry.
CVPR, June.
Mason W, 1997. Open-GL Programming Guide. Addison-
Wesley, 2 nd edition.
Mian G.A., Rinaldo R., 2000. Elaborazione e Trasmissione
delle Immagini. Ed. Libreria Progetto, Padova.
Nelson M., 1992. The Data Compression Book. M&T Books.
Ziv J., Lempel A., 1977. A Universal Algorithm for
Sequential Data Compression. IEEE Transactions on
Information Theory, n. 23, pp. 337-343.