Image Space Rendering of Point Clouds Using the HPR Operator

Silva, R. Machado e; Esperança, Cláudio; Marroquim, Ricardo; Oliveira, A.

doi:10.1111/cgf.12265

Cited by 6 publications

(6 citation statements)

References 24 publications

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“…In particular, we believe that particle‐based simulations involving surface tension [AAT13] and surface turbulence [MBT*15] can greatly benefit from our methodology. In terms of rendering, we want to investigate the surface reconstruction in screen space using an image‐based implementation of the HPR operator [MeSEMO14]. Finally, since our method is built upon local visibility tests, adapting it to GPU architecture is feasible, being another direction for future work.…”

Section: Discussionmentioning

confidence: 99%

Boundary Detection in Particle‐based Fluids

Sandim¹,

Cedrim²,

Nonato³

et al. 2016

Computer Graphics Forum

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Figure 1: The boundary particles (red) detected by our method in a cutaway view of a dam break with Bunny as obstacle. AbstractThis paper presents a novel method to detect free-surfaces on particle-based volume representation. In contrast to most particlebased free-surface detection methods, which perform the surface identification based on physical and geometrical properties derived from the underlying fluid flow simulation, the proposed approach only demands the spatial location of the particles to properly recognize surface particles, avoiding even the use of kernels. Boundary particles are identified through a Hidden Point Removal (HPR) operator used for visibility test. Our method is very simple, fast, easy to implement and robust to changes in the distribution of particles, even when facing large deformation of the free-surface. A set of comparisons against state-of-the-art boundary detection methods show the effectiveness of our approach. The good performance of our method is also attested in the context of fluid flow simulation involving free-surface, mainly when using level-sets for rendering purposes.

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Section: Discussionmentioning

confidence: 99%

Boundary Detection in Particle‐based Fluids

Sandim¹,

Cedrim²,

Nonato³

et al. 2016

Computer Graphics Forum

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“…The operator is a simple algorithm to determine visibility in point clouds without performing surface reconstruction. It first transforms the points of the cloud by means of spherical flipping inversion, and then computes the convex hull of the set containing the viewpoint and the transformed points [35]. A point is then marked visible from a given point of view if its inverted point lies on the convex hull ( Figure 3) [33].…”

Section: Visibility Analysismentioning

confidence: 99%

“…Straightforward solutions are in fact bound to fail, and calculating the LOS between two point is not helpful since, except for extreme cases, a point is always visible, even with high-resolution point clouds. The method has found numerous applications in several domains, is supported by theoretical guarantees, and was explained in depth by Katz et al [33][34][35][36]. R, the radius of the sphere for spherical flipping, is the only parameter to set.…”

Section: Visibility Analysismentioning

confidence: 99%

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Optimizing Wireless Sensor Network Installations by Visibility Analysis on 3D Point Clouds

Gracchi

Gigli

Noël

et al. 2019

IJGI

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In this paper, a MATLAB tool for the automatic detection of the best locations to install a wireless sensor network (WSN) is presented. The implemented code works directly on high-resolution 3D point clouds and aims to help in positioning sensors that are part of a network requiring inter-visibility, namely, a clear line of sight (LOS). Indeed, with the development of LiDAR and Structure from Motion technologies, there is an opportunity to directly use 3D point cloud data to perform visibility analyses. By doing so, many disadvantages of traditional modelling and analysis methods can be bypassed. The algorithm points out the optimal deployment of devices following mainly two criteria: inter-visibility (using a modified version of the Hidden Point Removal operator) and inter-distance. Furthermore, an option to prioritize significant areas is provided. The proposed method was first validated on an artificial 3D model, and then on a landslide 3D point cloud acquired from terrestrial laser scanning for the real positioning of an ultrawide-band WSN already installed in 2016. The comparison between collected data and data acquired by the WSN installed following traditional patterns has demonstrated its ability for the optimal deployment of a WSN requiring inter-visibility.integrated with sensors that can gather information through wireless links [7]. Their use presents several advantages over traditional monitoring techniques, such as the capability to work in rough and hardly accessible terrain, thanks to the absence of wired structures [8]; the possibility to analyze data from a multipoint perspective [9]; the ease and speed of installation [10]; and the adaptability of sensors to be integrated with existing monitoring techniques [11,12]. To make the most out of a WSN, optimal sensor deployment (i.e., equal and thoughtful distribution) is essential, and, to this aim, sensor-deployment problems were studied in several contexts [13]. For instance, Wang et al. [14] geometrically analyzed the relationship between coverage and connectivity in a WSN considering an obstacle-free environment, and Zou and Chakrabarty [15] proposed a virtual force algorithm as a sensor-deployment strategy after an initial random placement of sensors. For some types of sensors, line of sight (LOS) cannot be neglected. Information is in fact properly transmitted if the transmitter and receiver stations are in view of each other without any obstacle. The LOS of each emitting sensor is therefore an important issue to consider when positioning two or more receivers.Researchers are increasingly focusing on LOS-based WSNs that use the same signal both for communication and ranging purposes, allowing the relative distance between nodes to be detected and landslide deformation to be assessed [16][17][18][19]. Depending mainly on their wavelength and the characteristics of the material to cross, waves can follow several types of behavior, and problems connected to unfavorable LOS may lead to the absence of data or inaccurate measurements due to a delay ...

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“…Em 2012 Machado e Silva et al [MeSEO12], publicaram um trabalho que apresenta uma implementação em GPU de um algoritmo para o cálculo do fecho convexo usado pelo operador HPR para tornar viável seu uso em aplicações interativas. Recentemente foi publicada também uma extensão desse trabalho [MeSEMO14] que inclui também amostragem de nuvem de pontos e realização de operações no espaço de imagem. Em 2013 um trabalho também feito por Katz et al [KT13] apresenta um problema considerado dual ao operador HPR, chamado de Target Point Occlusion -TPO, que tem como objetivo buscar pontos que causem a oclusão de um ponto específico a partir de observadores no infinito.…”

Section: Extensões E Trabalhos Relacionadosunclassified

Detecção de fronteira em sistemas de partículas

Sandim¹

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M simulações físicas baseadas em partículas, a informação sobre quais partículas pertencemà fronteira do sistema e quais são consideradas internasé, em geral, uma informaçãoútil porém difícil de ser obtida eficientemente. Esta informação pode ser usada na geração da superfície livre de um fluido ou no cálculo da tensão superficial do mesmo, entre outras aplicações. Técnicas encontradas na literatura podem apresentar resultados satisfatórios, mas em geral são sensíveisà escala do problema, distribuição das partículas e envolvem operações computacionalmente caras como inversão de matrizes. O objetivo deste trabalhoé estudar os métodos existentes e apresentar uma alternativa com custo computacional mais baixo e que seja capaz de lidar com problemas de diferentes escalas e naturezas de forma mais simples que os métodos existentes.

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Image Space Rendering of Point Clouds Using the HPR Operator

Cited by 6 publications

References 24 publications

Boundary Detection in Particle‐based Fluids

Boundary Detection in Particle‐based Fluids

Optimizing Wireless Sensor Network Installations by Visibility Analysis on 3D Point Clouds

Detecção de fronteira em sistemas de partículas

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