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# lec05 - 6.851 Advanced Data Structures Spring 2010 Lecture...

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6.851: Advanced Data Structures Spring 2010 Lecture 5 — Feb 18 th , 2010 Prof. Erik Demaine and Dr. Andr´ e Schulz Scribe: David Stein and Jacob Steinhardt 1 Overview In the last lecture we started out by briefy discussing range trees (a topic we started two lectures ago). In particular, we showed how to support dynamic insertions and deletions in range trees eFciently. A±ter this, we discussed the vertical line stabbing problem — given a collection o± intervals, support queries o± the ±orm “How many intervals intersect the line x = x 0 ?”. We showed that both interval trees and segment trees could solve this problem eFciently. Segment trees are a bit more memory-eFcient, but interval trees are more fexible ±or other applications. We used these data structures to solve the windowing problem — given a collection o± line segments, report how many lie in a given axis-aligned rectangle. In solving the windowing problem, we had to introduce an additional data structure called a priority search tree . In this lecture we study kinetic data structures. These are data structures that contain in±ormation about objects in motion. They support the ±ollowing three types o± queries: (i) modi±y the motion path o± an object; (ii) move ±orward to a speci²ed point in time; (iii) return in±ormation about the state o± the objects in the current time. We will go over kinetic sorting and kinetic heaps, and then state several results about kinetic data structures without proo±. A±ter covering kinetic data structures, we will discuss the ray shooting problem — given a simple (possibly non-convex) polygon, support queries asking ±or the ²rst point o± intersection o± a ray with the polygon. We will show how to support O (log 2 ( n )) queries and outline an approach ±or achieving a query time o± O (log( n )). 2 Kinetic Data Structures 2.1 Introduction A kinetic data structure is a data structure that stores moving data — that is, data that changes in some predictable way over time. Examples would be the locations o± physical objects over time. We could also look at, ±or example, trajectories o± objects in R 2 and think o± the x -coordinate as “time.” Kinetic data structures are use±ul, ±or example, in computer graphics and video games, to determine the next point in time at which two objects intersect. Data. Each data point has a value that is a known ±unction o± time. ³or example, we could have aFne data ( x ( t ) = a + bt ). We could also have bounded-degree algebraic motion, or, more generally, pseudo-algebraic motion. Pseudo-algebraic means that all certi²cates o± interest fip between true or ±alse O (1) times as the objects move. It turns out that pseudo-algebraic will be the condition that we generally need in order ±or our kinetic data structures to run eFciently.

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lec05 - 6.851 Advanced Data Structures Spring 2010 Lecture...

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