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Introduction

Introduction. General Data Structures - Arrays, Linked Lists - Stacks & Queues - Hash Tables & Binary Search Trees - Graphs Spatial Data Structures Why care? Binary Space Partitioning (BSP) trees. Arrays & Linked Lists.

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Introduction

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  1. Introduction General Data Structures - Arrays, Linked Lists - Stacks & Queues - Hash Tables & Binary Search Trees - Graphs Spatial Data Structures Why care? Binary Space Partitioning (BSP) trees

  2. Arrays & Linked Lists 2D arrays and linked lists are used as: - Single and multi- layered Tile maps in 2D scenes in which each tile acts like a pixel. - Terrain maps in 3D world where 2D array represents the height of each tile in a level. Utility: - Abstracts the idea of pixels to a higher level significantly simplifying a drawing engine: - Linked Lists can be used for inventory

  3. Stacks & Queues Stacks: used to construct Menu, Submenus Queues: used for command queuing e.g. Real Time Strategy (RTS) games such as Command & Conquer, War craft, Star craft: Demo-5 Trade Off: When expandability is more important than speed, use linked stacks and queues; otherwise use arrayed stacks and queues.

  4. Others.. Hash Tables & Binary Search Trees: - searching; Trees: - Map editor (hierarchy of maps); - Skill system like RPGs such as Diablo 2 do. option to choose the skills e.g. healing skills or fighting skills. Graphs: - Portal Engine; games like Descent, Quake 2. more efficient method for rendering things:Demo-7

  5. Spatial Partitioning • What do we mean by spatial partitioning? Spatial partitioning mean dividing up the game world into regions that can be used to find spatial relationships between objects. • Why do we need spatial partitioning? Scenegraphs are great for recording the dynamic relationships between dynamic objects, e.g. parts of a body. They are not so good for storing information about static elements in a game world, e.g. walls in a building.

  6. Using Spatial Partitioning Spatial partitioning data structures are used to: • Determine which parts of large static objects are visible, e.g. buildings, terrains. • Determine neighborhood relationships between dynamic objects, e.g. for collision detection. • Determine how much data needs to be sent across a network, e.g. based on what is currently visible to the client.

  7. Spatial data Structures Spatial data structures store data indexed in some way by their spatial location • For instance, store points according to their location, or polygons, … • Before graphics, used for queries like “Where is the nearest hotel?” or “Which stars are strong enough to influence the sun?”

  8. Applications • Multitude of uses in computer games • Visibility - What can I see? • Ray intersections - What did the player just shoot? • Collision detection - Did the player just hit a wall? • Proximity queries - Where is the nearest power-up?

  9. Spatial Partitioning Schemes Two common spatial partitioning schemes are: - Binary Space Partitioning (BSP) - Quadtree/Octree Partitioning The partitioning schemes are similar in some ways, both: - Recursively subdivide a space into smaller spaces - Construct tree data-structure that can be searched quickly - Are expensive to modify, hence they are best used for static features of a world when they can be pre-computed once

  10. Binary Space Partitioning • Binary space partitioning works by dividing a space into two subspaces at each recursion with a plane • Choosing the best plane to divide a given space into two equally complex subspaces is the most difficult part. • Most game engines analyze the geometry of a world and choose an existing polygon to define a plane. • The analysis should determine which polygon will result in the most balanced tree.

  11. Binary Space Partitioning Example • Suppose that this figure - 1 represents the walls of a building in a game • We want to pre-process this complex shape into a BSP tree consisting of simpler regions to assist real-time rendering

  12. Walls of a building as space

  13. First subdivision: Split occurs at polygon 16

  14. Second subdivision: Split at polygon 4, 21

  15. Final BSP tree

  16. Choosing Splitting Planes • Goals: • Trees with few cells • Planes that are mostly opaque (best for visibility calculations) • Objects not split across cells • Some heuristics: • Choose planes that are also polygon planes • Choose large polygons first • Choose planes that don’t split many polygons • Try to choose planes that evenly divide the data • Let the user select or otherwise guide the splitting process • Random choice of splitting planes doesn’t do too badly

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