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DYNAMIC MODIFICATION OF COLLISION BOXES USING DATA-MINING TECHNIQUES By: James Ross

Dynamic Modification of Collision Boxes Using Data-Mining Techniques

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By: James Ross. Dynamic Modification of Collision Boxes Using Data-Mining Techniques. Outline. Collision Conecpts Axis Aligned Bounding Box ECMs Objective Methodology Expected Results. Collision Concepts In Virtual Worlds. What is: Collision Detection Collision Mapping - PowerPoint PPT Presentation

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Page 1: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

DYNAMIC MODIFICATION OF COLLISION BOXES USING DATA-MINING TECHNIQUES

By: James Ross

Page 2: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Outline

Collision Conecpts Axis Aligned Bounding Box ECMs Objective Methodology Expected Results

Page 3: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Collision Concepts In Virtual Worlds

What is: Collision Detection Collision Mapping

Axis Aligned Bounding Box or AABB

Page 4: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Axis Aligned Bounding Box (AABB)

AABB – Collision Mapping Method MBR – Minimum

Bounding Rectangles Represents the spatial

extent of an object in the ECM

ECM – Expected Collision Map Areas a user cannot go

Page 5: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Current Methods: ECMs

Slow Require lots of interaction between

developer and tester Static

Once a collision map is developed it is never modified by adding objects

Page 6: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

ECMs In Collaborative Virtual Reality Environments (CVRE)

Primitive Objects Predefine collision

maps for primitive objects

User Added Objects Collisions maps are

often incorrect Extremely difficult for

developers to keep up with modifying incorrect collision maps

Page 7: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Objective Create a better

collision map dynamically without either restriction to a small set of assets or manually modification of every bounding box

Page 8: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Methodology

Create a virtual reality environment and add objects

Have the user explore the environment with the intention of not running into objects Store detected collisions in a data-set

Page 9: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Methodology

Algorithm examines the data-set to: Detect unusual user-ECM interactions Separate accidental collision data from

problem collision areas Iteratively improve MBRs with identified

collision problems

Page 10: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Methodology

Dynamically generate a new trial MBR for the offending object

User Interactions and immersion into the environment

Page 11: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Expected Results

The development of a new approach to automated ECM improvement in CVRE will enable a new generation of open environments in which users can contribute arbitrary objects to the environment and regular manual revisions of bounding boxes in unnecessary

Page 12: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Expected Results

Improve the speed in which AABB collision maps are created Less time spent by collision map

developers Less time spent by environment testers

Help take the collision map modification out of the hands of the developer and modify the environment based on the expected path of the user

Page 13: Dynamic Modification of Collision Boxes Using Data-Mining Techniques

Questions?