Luo Zhenshan, Zhang Junsong, Fan Jiepeng. Synthesizing multi-destinations map with factor graph[J]. Journal of Image and Graphics, 2015, 20(3): 418-426.DOI: 10.11834/jig.20150313.
Synthesizing multi-destinations map with factor graph
An increasing number of people usually need to work or take a holiday with their families in another city. Therefore
having an accurate map is necessary when they arrive in an unfamiliar city. Some online maps
such as Baidu or Google
can provide sufficient but redundant information. Users only need some information about their destinations
but excessive details on other places give rise to difficulty in reading maps. Meanwhile
users often need to perform many tedious operations
such as zoom in and zoom out
to obtain useful information. Therefore
we present a factor graph-based method to generate multiple destinations maps. This method can provide users with only useful information so that they can obtain help easily. Our method consists of three steps. First
users select multiple destinations of interest. The detail of some areas that are far from the user destinations is unnecessary. Second
the proposed system automatically selects the most relevant subset of roads that are related to the destinations according to certain predefined guidelines. These guidelines ensure that the selected road network maintains conciseness and connectivity so that users can arrive at any destination. Finally
the layout is adjusted to present an accurate map. The map should ensure that the details of the information on the destinations are clear while maintaining the original topology of the map. Moreover
we should maximize screen usage to display more information. Thus
we identify a set of design rules to constrain the map layout. We conduct some preprocessing of the road network to implement layout optimization. We segment the road network into several rectangular areas according to the user destinations. Every rectangle contains only one destination. During optimization
we can choose a rectangular area-based perturbation or point-based perturbation. Furthermore
we use factor graph
a type of graphical model
to improve algorithm efficiency by encoding constraints as factors. We obtain the desired map layout with the Metropolis-Hastings algorithm by sampling from the target distribution constructed by the factor graph. Online maps fail to provide selective information
whereas other maps
such as hand-drawn maps
often produce map deformation that affects map reading. The multi-destination maps generated by the proposed method not only provide users with detailed road information of multiple destinations in the same view while maintaining the topology among destinations. Moreover
unnecessary information is automatically omitted. In this study
we present a new method to generate maps with a factor graph. The factor graph can clearly describe the relationships of objects. Experiment results indicate that the proposed approach can efficiently solve the problem confronting online maps
which fail to provide users with sufficient and detailed information on multi-destinations in the same view.