On-line construction of the convex hull of a simple polyline
Information Processing Letters
Determining the minimum-area encasing rectangle for an arbitrary closed curve
Communications of the ACM
Location Privacy in Pervasive Computing
IEEE Pervasive Computing
Determining the Convex Hull in Large Multidimensional Databases
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
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Data collected from real world are often imprecise. A few algorithms were proposed recently to compute the convex hull of maximum area when the axis-aligned squares model is used to represent imprecise input data. If squares are non-overlapping and of different sizes, the time complexity of the best known algorithm is O(n7). If squares are allowed to overlap but have the same size, the time complexity of the best known algorithm is O(n5). In this paper, we improve both bounds by a quadratic factor, i.e., to O(n5) and O(n3), respectively.