Believability in simplifications of large scale physically based simulation

Han, Deguang; Hsu, Shu-Wei; McNamara, Ann; Keyser, John

doi:10.1145/2492494.2492504

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…show that a specific simplification of large scale rigid body simulation methods did not significantly influence the visual plausibility [HHMK13]. However, little prior work has considered deformable objects.…”

Section: Perception Of Physically Based Simulationmentioning

confidence: 88%

“…Reitsma and O'Sullivan further examine how a realistic environment setting can affect visual plausibility of physically based simulations [RO09]. Han et al show that a specific simplification of large scale rigid body simulation methods did not significantly influence the visual plausibility [HHMK13]. However, little prior work has considered deformable objects.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Low‐level Visual Details in Perception of Deformation

Han

Keyser

2016

Computer Graphics Forum

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Figure 1: Frames taken from two stimuli. They are rendered from a physically based simulation of deformable sphere models with differing Young's Modulus. We combine different levels of contrast and spatial frequency to create 25 different checkerboard textures, two of which are shown above. We further study how backgrounds can influence the effect of low-level visual details using stimuli like the lower one. AbstractWe quantitatively measure how different low-level visual details can influence people's perceived stiffness of a deformable sphere under physically based simulation. The result can be used to create a metric for artists in designing textures to enhance or reduce the stiffness perceived by a viewer. We use a checkerboard texture to render the simulation of a free falling sphere that collides with the ground and bounces up. We vary the spatial frequency and contrast of the checkerboard pattern according to results seen in a previous study on the Spatial-Temporal Contrast Sensitivity Function (CSF). We find that checkerboard pattern with certain combinations of spatial frequency and contrast can reduce the perceived stiffness. We also add a high contrast checkerboard background to study how complex backgrounds can influence the effect of low-level details in textures of foreground objects. Our study shows that the effect of low-level visual details in foreground objects observed previously disappears in this situation. This indicates the importance of background, even if it is static.

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Section: Perception Of Physically Based Simulationmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Effect of Low‐level Visual Details in Perception of Deformation

Han

Keyser

2016

Computer Graphics Forum

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“…Reitsma et al [2009] further examines how a realistic environment setting can affect visual plausibility of physically based simulations. Han et al [2013] shows that a specific simplification of large scale rigid body simulation methods does not significantly influence the visual plausibility. However, few works have considered deformable objects.…”

Section: Perception Of Physically Based Simulationmentioning

confidence: 96%

Effect of appearance on perception of deformation

Han

Keyser

2015

Proceedings of the 14th ACM SIGGRAPH / Eurographics Symposium on Computer Animation

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Figure 1: Frames taken from two animations of 64 objects. Both are rendered using the same physically based simulation of deformable cylinder models. Two appearances (Gastank and Sausage) are used for rendering. Both animations are used as stimuli in the study. Highlevel information in these static images hints at a rigid gastank and deformable sausage. In animation, however, low-level cues may allow deformations in the gastank to be perceived more easily. We study the potential influences using three user studies. AbstractWe provide an experimental validation that appearance of an object can influence the perception of its level of deformation in a 3D simulation. Our study provides helpful insights in how to improve visual plausibility of deformation, which may allow artists to adjust their designs to enhance or minimize the perceived deformation in a model. We use a physically-based deformation model to simulate simple geometric shapes undergoing deformation. We apply a number of different appearance and rendering parameters to these objects, and then use two user studies to measure whether appearance used for an object can have a statistically significant effect on the perception of its deformation. In another study, we adjust the number of objects simulated and investigate how this can influence the effect of appearance.We find that appearance can potentially influence people's sensitivity to differences of deformation as well as subjective rating of softness in our studies. Further analysis shows that, in simple scenarios, the effect of low-level cues in appearance can be dominant, even if high-level information delivered by appearance has the opposite implication. The third study shows that as the number of objects in a scenario increases, objects are perceived to be stiffer. Also, the effect of low-level cues is weaker.

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“…[21] present a constraint-based method to stabilize a stack of piles. [19] introduces a hypothesis for physical simulation simplification which is freezing transformations of objects in a random pile does not affect the visual plausibility of a simulation. However, none of them can be efficient enough for stability estimation in a DRL training framework.…”

Section: Related Workmentioning

confidence: 99%

Learning Practically Feasible Policies for Online 3D Bin Packing

Zhao¹,

Zhu²,

Xu³

et al. 2021

Preprint

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We tackle the Online 3D Bin Packing Problem, a challenging yet practically useful variant of the classical Bin Packing Problem. In this problem, the items are delivered to the agent without informing the full sequence information. Agent must directly pack these items into the target bin stably without changing their arrival order, and no further adjustment is permitted. Online 3D-BPP can be naturally formulated as Markov Decision Process (MDP). We adopt deep reinforcement learning, in particular, the on-policy actorcritic framework, to solve this MDP with constrained action space. To learn a practically feasible packing policy, we propose three critical designs. First, we propose an online analysis of packing stability based on a novel stacking tree. It attains a high analysis accuracy while reducing the computational complexity from O(N 2 ) to O(N log N ), making it especially suited for RL training. Second, we propose a decoupled packing policy learning for different dimensions of placement which enables high-resolution spatial discretization and hence high packing precision. Third, we introduce a reward function that dictates the robot to place items in a far-to-near order and therefore simplifies the collision avoidance in movement planning of the robotic arm. Furthermore, we provide a comprehensive discussion on several key implemental issues. The extensive evaluation demonstrates that our learned policy outperforms the state-of-the-art methods significantly and is practically usable for real-world applications.

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Believability in simplifications of large scale physically based simulation

Cited by 7 publications

References 25 publications

Effect of Low‐level Visual Details in Perception of Deformation

Effect of Low‐level Visual Details in Perception of Deformation

Effect of appearance on perception of deformation

Learning Practically Feasible Policies for Online 3D Bin Packing

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