TY - GEN
T1 - A zone-based approach for placing annotation labels on metro maps
AU - Wu, Hsiang Yun
AU - Takahashi, Shigeo
AU - Lin, Chun-Cheng
AU - Yen, Hsu Chun
PY - 2011/7/29
Y1 - 2011/7/29
N2 - Hand-drawn metro map illustrations often employ both internal and external labels in a way that they can assign enough information such as textual and image annotations to each landmark. Nonetheless, automatically tailoring the aesthetic layout of both textual and image labels together is still a challenging task, due to the complicated shape of the labeling space available around the metro network. In this paper, we present a zone-based approach for placing such annotation labels so that we can fully enhance the aesthetic criteria of the label arrangement. Our algorithm begins by decomposing the map domain into three different zones where we can limit the position of each label according to its type. The optimal positions of labels of each type are evaluated by referring to the zone segmentation over the map. Finally, a new genetic-based approach is introduced to compute the optimal layout of such annotation labels, where the order in which the labels are embedded into the map is improved through the evolutional computation algorithm. We also equipped a semantic zoom functionality, so that we can freely change the position and scale of the metro map.
AB - Hand-drawn metro map illustrations often employ both internal and external labels in a way that they can assign enough information such as textual and image annotations to each landmark. Nonetheless, automatically tailoring the aesthetic layout of both textual and image labels together is still a challenging task, due to the complicated shape of the labeling space available around the metro network. In this paper, we present a zone-based approach for placing such annotation labels so that we can fully enhance the aesthetic criteria of the label arrangement. Our algorithm begins by decomposing the map domain into three different zones where we can limit the position of each label according to its type. The optimal positions of labels of each type are evaluated by referring to the zone segmentation over the map. Finally, a new genetic-based approach is introduced to compute the optimal layout of such annotation labels, where the order in which the labels are embedded into the map is improved through the evolutional computation algorithm. We also equipped a semantic zoom functionality, so that we can freely change the position and scale of the metro map.
UR - http://www.scopus.com/inward/record.url?scp=79960741422&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22571-0_8
DO - 10.1007/978-3-642-22571-0_8
M3 - Conference contribution
AN - SCOPUS:79960741422
SN - 9783642225703
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 91
EP - 102
BT - Smart Graphics - 11th International Symposium, SG 2011, Proceedings
T2 - 11th International Symposium on Smart Graphics, SG 2011
Y2 - 18 July 2011 through 20 July 2011
ER -