Page 30 - 2024F
P. 30
UEC Int’l Mini-Conference No.53 23
considerable computational time and occasion- References
ally exhibits instability, particularly for large
datasets. Moreover, it relies on precomputed [1] B. Alsallakh, L. Micallef, W. Aigner,
optimization, which, while effective for static vi- H. Hauser, S. Miksch, and P. Rodgers, “The
sualizations, may not be suitable for interactive State‐of‐the‐Art of Set Visualization,” Com-
or real-time applications. puter Graphics Forum, vol. 35, pp. 234–260,
Feb. 2016.
Future research may focus on addressing these
limitations by proposing faster algorithms or ex- [2] B. Alper, N. Riche, G. Ramos, and M. Cz-
ploring adaptive algorithms that dynamically erwinski, “Design study of linesets, a novel
adjust curve layouts in response to user interac- set visualization technique,” IEEE Transac-
tions. Potential directions include parallel com- tions on Visualization and Computer Graph-
puting techniques and machine learning-based ics, vol. 17, no. 12, pp. 2259–2267, 2011.
approaches to improve computational efficiency
and stability. Additionally, for point sets with [3] D. Tranquille, G. Stapleton, J. Burton, and
non-fixed node positions, such as social net- P. J. Rodgers, “Evaluating the effects of
works, integrating curve optimization with point colour in linesets,” in Diagrams, 2016.
set layout optimization could further enhance [4] J. B. Dominique Tranquille, Gem Stapleton
the adaptability and effectiveness of the method, and P. Rodgers, “Evaluating graphical ma-
enabling more flexible and interactive visualiza- nipulations in automatically laid out line-
tion systems. sets,” Behaviour & Information Technology,
vol. 40, no. 4, pp. 361–384, 2021.
[5] M. Jiang, X. Zhang, Y. Wu, Y. Chen, and
6 Conclusion K. Qu, “Research status of curve smooth-
ing algorithm,” International Journal of Re-
search in Engineering and Science (IJRES),
This study presents an effective optimization
framework for LineSets visualizations, signifi- vol. 6, no. 8, pp. 50–53, 2018.
cantly improving clarity and readability. By [6] K. Helsgaun, “An extension of the lin-
minimizing maximum curvature, reducing curve kernighan-helsgaun tsp solver for con-
intersections, and increasing crossing angles, our strained traveling salesman and vehicle rout-
method enhances the interpretability of spatial ing problems,” tech. rep., Department of
and network-based visualization. The results Computer Science, Roskilde University, De-
demonstrate its potential in various applica- cember 2017.
tions, such as urban planning and social network
analysis. Future research could explore faster [7] W. Huang, P. Eades, and S.-H. Hong,
and adaptive algorithms for real-time applica- “Larger crossing angles make graphs easier
tions and integration with layout optimization to read,” Journal of Visual Languages &
for dynamic datasets. Computing, vol. 25, pp. 452–465, Aug. 2014.
[8] R. Cimurs, J. Hwang, and I. H. Suh,
“Bezier Curve-Based Smoothing for Path
Planner with Curvature Constraint,” in 2017
7 Acknowledgments First IEEE International Conference on
Robotic Computing (IRC), (Taichung, Tai-
The author is supported by the JASSO schol- wan), pp. 241–248, IEEE, Apr. 2017.
arship in the UEC JUSST Exchange Program. [9] D. Hermes, “Helper for bézier curves, trian-
The author would like to express special thanks gles, and higher order objects,” The Journal
to Professor Okamoto Yoshio, Professor Choo of Open Source Software, vol. 2, p. 267, Aug
C.K. and other colleagues for their support and 2017.
valuable suggestions.