Abstract
Readily available RGB-D cameras in smart phones and improving 3D scanning technologies have made it possible to produce detailed point cloud and point-based models of real world objects even in real time. Rendering such models in high quality and at satisfactory frame rates is needed for realistic <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">extended reality</i> (XR) applications. This publication reviews real-time photorealistic point cloud rendering methods which directly ray trace or rasterize point cloud models, with an emphasis on ray tracing and real-time performance. We found that real-time direct point cloud ray tracing research has been focused on static non-animated content, and thus, open research possibilities include adapting modern dedicated ray tracing hardware for increased performance for animated and live captured scenes, and adding path tracing techniques to increase photorealistic effects in the rendering result. A categorization and discussion on the capabilities of state-of-the-art photorealistic point cloud rendering methods is presented by surveying both real-time and offline methods, which are assumed to become real-time capable with the advances in near-future hardware. Challenges and future trends are derived by comparing different rasterization and ray tracing methods as well as acceleration structures for point clouds in terms of produced rendering effects and speed.
Highlights
Point cloud and point-based visualization have been studied for more than three decades
Close to this survey is the publication comparing different rasterization-based methods to meshed model rendering for real time point cloud visualization [32]
In the rest of this section we review the various ray tracing methods not covered in other literature that are capable of producing photorealism in a scene by rendering point clouds in real time
Summary
Point cloud and point-based visualization have been studied for more than three decades. The challenge in point cloud visualization has been the lack of a continuous surface representation. On the other hand, generating correct surface attributes between point cloud points in a rasterization pipeline needs special handling compared to the interpolation and intersection of values between vertices in a triangle or other polygonal-based model. This is true when finding an intersection point between a viewing ray and the implied surface representation of a point cloud.
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