Compressed Bounding Volume Hierarchies for Collision Detection Proximity Query

12/09/2020
by   Toni Tan, et al.
0

We present a novel representation of compressed data structure for simultaneous bounding volume hierarchy (BVH) traversals like they appear for instance in collision detection proximity query. The main idea is to compress bounding volume (BV) descriptors and cluster BVH into a smaller parts 'treelet' that fit into CPU cache while at the same time maintain random-access and automatic cache-aware data structure layouts. To do that, we quantify BV and compress 'treelet' using predictor-corrector scheme with the predictor at a specific node in the BVH based on the chain of BVs upwards.

READ FULL TEXT

page 1

page 2

page 3

research
04/17/2022

An n H_k-compressed searchable partial-sums data structure for static sequences of sublogarithmic positive integers

We consider the space needed to store a searchable partial-sums data str...
research
02/04/2022

Neural Collision Detection for Deformable Objects

We propose a neural network-based approach for collision detection with ...
research
03/12/2018

Reactive Proximity Data Structures for Graphs

We consider data structures for graphs where we maintain a subset of the...
research
09/26/2019

String Indexing with Compressed Patterns

Given a string S of length n, the classic string indexing problem is to ...
research
09/18/2017

Compressed Representations of Conjunctive Query Results

Relational queries, and in particular join queries, often generate large...
research
10/18/2018

Towards a compact representation of temporal rasters

Big research efforts have been devoted to efficiently manage spatio-temp...

Please sign up or login with your details

Forgot password? Click here to reset