We consider the 2-dimensional range searching problem in the case where all points lie on an integer grid. A new data structure is presented that solves range queries on a U * U grid in O( k + log log U) time using O( n log n) storage, where n is the number of points and k the number of reported answers. Although the query time is very good the preprocessing time of this method is very high. A ...

Given an initial rectangular range or k nearest neighbor (k-nn) query (using the L1 metric), we consider the problems of incrementally extending the query by increasing the size of the range, or by increasing k, and reporting the new points incorporated by each extension. Although both problems may be solved trivially by repeatedly applying a traditional range query or L1 k-nn algorithm, such s...

Given a set P of n uncertain points on the real line, each represented by its one-dimensional probability density function, we consider the problem of building data structures on P to answer range queries of the following three types for any query interval I : (1) top-1 query: find the point in P that lies in I with the highest probability, (2) top-k query: given any integer k ≤ n as part of th...

Given a set P of n coloured points on the real line, we study the problem of answering range α-majority (or “heavy hitter”) queries on P . More specifically, for a query range Q, we want to return each colour that is assigned to more than an α-fraction of the points contained in Q. We present a new data structure for answering range α-majority queries on a dynamic set of points, where α ∈ (0, 1...

Many visual difference predictors (VDPs) have used basic psychophysical data (such as ModelFest) to calibrate the algorithm parameters and to validate their performances. However, the basic psychophysical data often do not contain sufficient number of stimuli and its variations to test more complex components of a VDP. In this paper we calibrate the Visual Difference Predictor for High Dynamic ...

We study the orthogonal range searching problem on points that have a significant number of geometric repetitions, that is, subsets of points that are identical under translation. Such repetitions occur in scenarios such as image compression, GIS applications and in compactly representing sparse matrices and web graphs. Our contribution is twofold. First, we show how to compress geometric repet...

Recent advances in various application fields, like GIS, finance and others, has lead to a large increase in both the volume and the characteristics of the data being collected. Hence, general range queries on these datasets are not sufficient enough to obtain good insights and useful information from the data. This leads to the need for more sophisticated queries and hence novel data structure...

The mode of a multiset of labels, is a label that occurs at least as often as any other label. The input to the range mode problem is an array A of size n. A range query [i, j] must return the mode of the subarray A[i], A[i+ 1], . . . , A[j]. We prove that any data structure that uses S memory cells of w bits needs Ω( log n log(Sw/n) ) time to answer a range mode query. Secondly, we consider th...