Fast Collision Detection Method with Octree-Based Parallel Processing in Unity3D Article Swipe
Kunthroza Hor
,
Taeheon Kim
,
Min Hong
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/engproc2025089037
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/engproc2025089037
Performing accurate and precise collision detection is a key to real-time applications in computer graphics, games, physical-based simulation, virtual reality, augmented reality, and research and development. Researchers have developed numerous methods to minimize computation time and enhance the accuracy of collision detection for pair-object collisions. Although the performance of the central processing unit (CPU) has significantly improved in recent years, it is still insufficient for many applications. In this study, we have developed an improved algorithm for geometric bounding volume hierarchy (BHV) in 3D spatial subdivisions using an Octree-based axis-aligned bounding box (AABB) structure. The AABB structure is used for collision detection and its computation by the central processing unit and graphic processing unit (GPU), which is implemented on the compute shader in Unity3D. AABB was defined as the maximum and minimum hexahedron within an object that is parallel to the coordinate axis. While GPU computing is essential for enhancing the object’s performance. The proposed algorithm approaches Octree AABB-based GPU parallel processing to reduce the calculation or process of simulation for real-time collision detection and handles multiple computations. In the CPU environment, the algorithm spent 2.9 fps when simulating up to 20 objects of the Torus Model that contains 2.3 K vertices and 4.6 K triangles. In the GPU environment, it spent 635.62 fps with 20 objects, and the maximum number increased to 180 objects in real-time.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/engproc2025089037
- https://www.mdpi.com/2673-4591/89/1/37/pdf?version=1741939689
- OA Status
- gold
- Cited By
- 1
- References
- 10
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408466588
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4408466588Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/engproc2025089037Digital Object Identifier
- Title
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Fast Collision Detection Method with Octree-Based Parallel Processing in Unity3DWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-03-13Full publication date if available
- Authors
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Kunthroza Hor, Taeheon Kim, Min HongList of authors in order
- Landing page
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https://doi.org/10.3390/engproc2025089037Publisher landing page
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https://www.mdpi.com/2673-4591/89/1/37/pdf?version=1741939689Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2673-4591/89/1/37/pdf?version=1741939689Direct OA link when available
- Concepts
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Octree, Computer science, Collision detection, Collision, Computer graphics (images), Parallel computing, Artificial intelligence, Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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10Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.simulation, | 17 |
| abstract_inverted_index.Octree-based | 88 |
| abstract_inverted_index.applications | 11 |
| abstract_inverted_index.axis-aligned | 89 |
| abstract_inverted_index.development. | 25 |
| abstract_inverted_index.environment, | 181, 209 |
| abstract_inverted_index.insufficient | 63 |
| abstract_inverted_index.performance. | 152 |
| abstract_inverted_index.subdivisions | 85 |
| abstract_inverted_index.applications. | 66 |
| abstract_inverted_index.computations. | 177 |
| abstract_inverted_index.significantly | 55 |
| abstract_inverted_index.physical-based | 16 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5006130083 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I24541011 |
| citation_normalized_percentile.value | 0.84688931 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |