An Inverse Procedural Modeling Pipeline for SVBRDF Maps

Procedural modeling is now the de facto standard of material modeling in industry. Procedural models can be edited and are easily extended, unlike pixel-based representations of captured materials. In this article, we present a semi-automatic pipeline for general material proceduralization. Given Spatially Varying Bidirectional Reflectance Distribution Functions (SVBRDFs) represented as sets of pixel maps, our pipeline decomposes them into a tree of sub-materials whose spatial distributions are encoded by their associated mask maps. This semi-automatic decomposition of material maps progresses hierarchically, driven by our new spectrum-aware material matting and instance-based decomposition methods. Each decomposed sub-material is proceduralized by a novel multi-layer noise model to capture local variations at different scales. Spatial distributions of these sub-materials are modeled either by a by-example inverse synthesis method recovering Point Process Texture Basis Functions (PPTBF) [ 30 ] or via random sampling. To reconstruct procedural material maps, we propose a differentiable rendering-based optimization that recomposes all generated procedures together to maximize the similarity between our procedural models and the input material pixel maps. We evaluate our pipeline on a variety of synthetic and real materials. We demonstrate our method’s capacity to process a wide range of material types, eliminating the need for artist designed material graphs required in previous work [ 38 , 53 ]. As fully procedural models, our results expand to arbitrary resolution and enable high-level user control of appearance.

Comparable human spatial memory distortions in physical, desktop virtual and immersive virtual environments

Boundaries define regions of space and are integral to episodic memories. The impact of boundaries on spatial memory and neural representations of space has been extensively studied in freely-moving rodents. But less is known in humans and many prior studies have employed desktop virtual reality (VR) which lacks the body-based self-motion cues of the physical world, diminishing the potentially strong input from path integration to spatial memory. We replicated a desktop-VR study testing the impact of boundaries on spatial memory (Hartley et al., 2004) in a physical room (2.4m x 2.4m, 2m tall) by having participants (N = 27) learn the location of a circular stool and then after a short delay replace it where they thought they had found it. During the delay, the wall boundaries were either expanded or contracted. We compared performance to groups of participants undergoing the same procedure in a laser-scanned replica in both desktop VR (N = 44) and freely-walking head mounted display (HMD) VR (N = 39) environments. Performance was measured as goodness of fit between the spatial distributions of group responses and seven modelled distributions that prioritised different metrics based on boundary geometry or walking paths to estimate the stool location. The best fitting model was a weighted linear combination of all the geometric spatial models, but an individual model derived from place cell firing in Hartley et al. 2004 also fit well. High levels of disorientation in all three environments prevented detailed analysis on the contribution of path integration. We found identical model fits across the three environments, though desktop VR and HMD-VR appeared more consistent in spatial distributions of group responses than the physical environment and displayed known variations in virtual depth perception. Thus, while human spatial representation appears differentially influenced by environmental boundaries, the influence is similar across virtual and physical environments. Despite differences in body-based cue availability, desktop and HMD-VR allow a good and interchangeable approximation for examining human spatial memory in small-scale physical environments.

Predicting changes in molluscan spatial distributions in mangrove forests in response to sea-level rise

Molluscs are an important component of the mangrove ecosystem, and the vertical distributions of molluscan species in this ecosystem are primarily dictated by tidal inundation. Thus, sea-level rise (SLR) may have profound effects on mangrove mollusc communities. Here, we used two dynamic empirical models based on measurements of surface elevation change, sediment accretion and zonation patterns of molluscs to predict changes in molluscan spatial distributions in response to different sea-level rise rates in the mangrove forests of Zhenzhu Bay (Guangxi, China). The change in surface elevation was 4.76–9.61 mm a during the study period (2016–2020), and the magnitude of surface-elevation change decreased exponentially as original surface elevation increased. Based on our model results, we predicted that mangrove molluscs might successfully adapt to a low rate of SLR (marker-horizon model: 2–4.57 mm a; plate model: 2–5.20 mm a) by 2100, with molluscs moving seaward and those in the lower intertidal zones expanding into newly available zones. However, as SLR rate increased (marker-horizon model: 4.57–8.14 mm a; plate model: 5.20–6.88 mm a), our models predicted that surface elevations would decrease beginning in the high intertidal zones and gradually spreading to the low intertidal zones. Finally, at high rates of SLR (marker-horizon model: 8.14–16.00 mm a; plate model: 6.88–16.00 mm a), surface elevations were predicted to decrease across the elevation gradient, with molluscs moving landward and species in higher intertidal zones would be blocked by landward barriers. Tidal inundation and the consequent increase in interspecific competition and predation pressure were predicted to threaten the survival of many molluscan groups in higher intertidal zones, especially species at the landward edge of the mangroves. Thus, future efforts to conserve mangrove floral and faunal diversity should prioritize species restricted to landward mangrove areas.

Lemaître's law and the spatial distributions of the cone photoreceptors in the retinas of vertebrates

By applying the principle of maximum entropy, we demonstrate the universality of the spatial distributions of the cone photoreceptors in the retinas of vertebrates. We obtain Lemaître's law as a special case of our formalism.

Volatile Abundances, Extended Coma Sources, and Nucleus Ice Associations in Comet C/2014 Q2 (Lovejoy)

High-resolution infrared spectra of comet C/2014 Q2 Lovejoy were acquired with NIRSPEC at the W. M. Keck Observatory on two post-perihelion dates (UT 2015 February 2 and 3). H2O was measured simultaneously with CO, CH3OH, H2CO, CH4, C2H6, C2H4, C2H2, HCN, and NH3 on both dates, and rotational temperatures, production rates, relative abundances, H2O ortho-to-para ratios, and spatial distributions in the coma were determined. The first detection of C2H4 in a comet from ground-based observations is reported. Abundances relative to H2O for all species were found to be in the typical range compared with values for other comets in the overall population to date. There is evidence of variability in rotational temperatures and production rates on timescales that are small compared with the rotational period of the comet. Spatial distributions of volatiles in the coma suggest complex outgassing behavior. CH3OH, HCN, C2H6, and CH4 spatial distributions in the coma are consistent with direct release from associated ices in the nucleus and are peaked in a more sunward direction compared with co-measured dust. H2O spatial profiles are clearly distinct from these other four species, likely due to a sizable coma contribution from icy grain sublimation. Spatial distributions for C2H2, H2CO, and NH3 suggest substantial contributions from extended coma sources, providing further evidence for distinct origins and associations for these species in comets. CO shows a different spatial distribution compared with other volatiles, consistent with jet activity from discrete nucleus ice sources.

Variability and probabilistic estimates of rainfall extremes In Bangladesh during the southwest monsoon season

The present study describes the temporal and spatial distributions of mean monthly rainfall and its variability together with the spatial distributions of the probabilistic estimates of rainfall extremes over Bangladesh during the- southwest monsoon season. The- probabilistic rainfall extremes have been computed for IWO lime scales: (a) in I year out of 4 years, and (b) in 1 year out of 10 years -representing relatively less extreme events and extreme events respectively. The mean monthly rainfall increases from June to July at most places over Bangladesh and then decreases up to September. The variability of rainfall decreases with increasing rainfall up to July at many places and then increases up to September. The study also reveals that the mean rainfall and the- probabilistic rainfall extremes are maximum over the southern and north-eastern parts of the country where the variability of rainfall is low and the rainfall is reliable. There exists a belt of low rainfall over the- central part of Bangladesh roughly between 23oN and 24°N. The rainfall gradients are maximum over north-eastern Bangladesh and the gradients of the probabilistic high rainfall are more than those of the probabilistic low rainfall in this area.