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In this paper, we consider the problem of computing the visibility polygon (VP) of a query point q (or VP(q)) in a scene consisting of some obstacles with total complexity of n. We show that the combinatorial representation of VP(q) can be computed in logarithmic time by preprocessing the scene in O( n4logn) time and using O( n4) space. We can also report the actual VP(q) in additional O(|VP(q)|) time. As a main result of this paper, we will prove that we can have a tradeoff between the query time and the preprocessing time/space. In other words, we will show that using O(m) space, we can obtain O( n2log(m/n)/m) query time, where m is a parameter satisfying n2≤m≤ n4. For example, when m= n3,... 

We study a new class of visibility problems based on the notion of α-visibility. Given an angle α and a collection of line segments in the plane, a segment t is said to be α-visible from a point p, if there exists an empty triangle with one vertex at p and the side opposite to p on t such that the angle at p is α. In this model of visibility, we study the classical variants of point visibility, weak and complete segment visibility, and the construction of the visibility graph. We also investigate the natural query versions of these problems, when α is either fixed or specified at query time  

Computing the visibility polygon, VP, of a point in a polygonal scene, is a classical problem that has been studied extensively. In this paper, we consider the problem of computing VP for any query point efficiently, with some additional preprocessing phase. The scene consists of a set of obstacles, of total complexity O(n). We show for a query point q, VP(q) can be computed in logarithmic time using O(n 4) space and O(n 4 logn) preprocessing time. Furthermore to decrease space usage and preprocessing time, we make a tradeoff between space usage and query time; so by spending O(m) space, we can achieve O(n 2 log √ m/n)/√ m)query time, where n 2≤m≤n 4. These results are also applied to... 

We study a new class of visibility problems based on the notion of α-visibility. Given an angle α and a collection of line segments S in the plane, a segment t is said to be α-visible from a point p, if there exists an empty triangle with one vertex at p and the side opposite to p on t such that the angle at p is α. In this model of visibility, we study the classical variants of point visibility, weak and complete segment visibility, and the construction of the visibility graph. We also investigate the natural query versions of these problems, when α is either fixed or specified at query time  

In this paper, we study the problem of finding the shortest path between two points inside a simple polygon such that there is at least one point on the path from which a query point is visible. We provide an algorithm which preprocesses the input in O (n2 + n K) time and space and provides logarithmic query time. The input polygon has n vertices and K is a parameter dependent on the input polygon which is O (n2) in the worst case but is much smaller for most polygons. The preprocessing algorithm sweeps an angular interval around every reflex vertex of the polygon to store the optimal contact points between the shortest paths and the windows separating the visibility polygons of the query... 

For a set of n disjoint line segments S in R2, the visibility counting problem (VCP) is to preprocess S such that the number of visible segments in S from a query point p can be computed quickly. For this configuration, the visibility testing problem (VTP) is to test whether p sees a fixed segment s. These problems can be solved in logarithmic query time by using O(n4) preprocessing time and space. In this paper, we approximately solve this problem using quadratic preprocessing time and space. Our methods are superior to current approximation algorithms in terms of both approximation factor and preprocessing cost. In this paper, we propose a 2-approximation algorithm for the VCP using at... 

For a simple polygon P of size n, we define weak visibility counting problem (WVCP) as finding the number of visible segments of P from a query line segment pq. We present different algorithms to compute WVCP in sub-linear time. In our first algorithm, we spend O(n7) time to preprocess the polygon and build a data structure of size O(n6), so that we can optimally answer WVCP in O(logn) time. Then, we reduce the preprocessing costs to O(n4+ε) time and space at the expense of more query time of O(log5n). We also obtain a trade-off between preprocessing and query time costs. Finally, we propose an approximation method to reduce the preprocessing costs to O(n2) time and space and O(n1/2+ε) query... 

In this paper we consider the problem of computing the weak visibility polygon of a query line segment pq (or (Formula presented.)) inside a given polygon (Formula presented.). Our first algorithm runs in simple polygons and needs (Formula presented.) time and (Formula presented.) space in the preprocessing phase to report (Formula presented.) of any query line segment pq in time (Formula presented.). We also give an algorithm to compute the weak visibility polygon of a query line segment in a non-simple polygon with (Formula presented.) pairwise-disjoint polygonal obstacles with a total of n vertices. Our algorithm needs (Formula presented.) time and (Formula presented.) space in the... 

In this paper we consider the problem of computing the weak visibility polygon of a query line segment pq (or WVP(pq)) inside a given polygon P. Our first algorithm runs in simple polygons and needs O(n3 log n) time and O(n3) space in the preprocessing phase to report WVP(pq) of any query line segment pq in time O(log n + |WVP(pq)|).. We also give an algorithm to compute the weak visibility polygon of a query line segment in a non-simple polygon with h ≥ 1 pairwise-disjoint polygonal obstacles with a total of n vertices. Our algorithm needs O(n2 log n) time and O(n2) space in the preprocessing phase and WVP(pq) in query time of O(nh’ log n + k), in which h’ is an output sensitive parameter...