BRDF Representation and Acquisition

Photorealistic rendering of real world environments is important in a range of different areas; including Visual Special effects, Interior/Exterior Modelling, Architectural Modelling, Cultural Heritage, Computer Games and Automotive Design. Currently, rendering systems are able to produce photorealistic simulations of the appearance of many real-world materials. In the real world, viewer perception of objects depends on the lighting and object/material/surface characteristics, the way a surface interacts with the light and on how the light is reflected, scattered, absorbed by the surface and the impact these characteristics have on material appearance. In order to re-produce this, it is necessary to understand how materials interact with light. Thus the representation and acquisition of material models has become such an active research area. This survey of the state-of-the-art of BRDF Representation and Acquisition presents an overview of BRDF (Bidirectional Reflectance Distribution Function) models used to represent surface/material reflection characteristics, and describes current acquisition methods for the capture and rendering of photorealistic materials

BRDF representation and acquisition

Photorealistic rendering of real world environments is important in a range of different areas; including Visual Special effects, Interior/Exterior Modelling, Architectural Modelling, Cultural Heritage, Computer Games and Automotive Design. Currently, rendering systems are able to produce photorealistic simulations of the appearance of many real-world materials. In the real world, viewer perception of objects depends on the lighting and object/material/surface characteristics, the way a surface interacts with the light and on how the light is reflected, scattered, absorbed by the surface and the impact these characteristics have on material appearance. In order to re-produce this, it is necessary to understand how materials interact with light. Thus the representation and acquisition of material models has become such an active research area. This survey of the state-of-the-art of BRDF Representation and Acquisition presents an overview of BRDF (Bidirectional Reflectance Distribution Function) models used to represent surface/material reflection characteristics, and describes current acquisition methods for the capture and rendering of photorealistic materials

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Towards a Consistent, Tool Independent Virtual Material Appearance

Current materials appearance is mainly tool dependent and requires time, labour and computational cost to deliver consistent visual result. Within the industry, the development of a project is often based on a virtual model, which is usually developed by means of a collaboration among several departments, which exchange data. Unfortunately, a virtual material in most cases does not appear the same as the original once imported in a different renderer due to different algorithms and settings. The aim of this research is to provide artists with a general solution, applicable regardless the file format and the software used, thus allowing them to uniform the output of the renderer they use with a reference application, arbitrarily selected within an industry, to which all the renderings obtained with other software will be made visually uniform. We propose to characterize the appearance of several classes of materials rendered using the arbitrary reference software by extracting relevant visual characteristics. By repeating the same process for any other renderer we are able to derive ad-hoc mapping functions between the two renderers. Our approach allows us to hallucinate the appearance of a scene, depicting mainly the selected classes of materials, under the reference software

Towards a consistent, tool independent virtual material appearance

Current materials appearance is mainly tool dependent and requires time, labour and computational cost to deliver consistent visual result. Within the industry, the development of a project is often based on a virtual model, which is usually developed by means of a collaboration among several departments, which exchange data. Unfortunately, a virtual material in most cases does not appear the same as the original once imported in a different renderer due to different algorithms and settings. The aim of this research is to provide artists with a general solution, applicable regardless the file format and the software used, thus allowing them to uniform the output of the renderer they use with a reference application, arbitrarily selected within an industry, to which all the renderings obtained with other software will be made visually uniform. We propose to characterize the appearance of several classes of materials rendered using the arbitrary reference software by extracting relevant visual characteristics. By repeating the same process for any other renderer we are able to derive ad-hoc mapping functions between the two renderers. Our approach allows us to hallucinate the appearance of a scene, depicting mainly the selected classes of materials, under the reference software

Machine learning reveals different brain activities in visual pathway during TOVA Test

This paper explores the changes in EEG when subjects performed a modified Test of Variables of Attention (TOVA), compared to open eye resting (baseline) state. To recognize these two different brain states, two machine learning algorithms, i.e. extreme learning machine (ELM) and support vector machine (SVM), were applied and compared, using 3 statistical features and 4 power spectral density per channel. The results showed that using all 14 channels, ELM and SVM achieved similar test accuracy of 94.6% and 95.1% respectively (McNemar's test p = 0.8 > 0.05). Using recursive channel selection, 9 channels (ELM) and 8 channels (SVM) were selected from 14 channels. After channel selection, ELM outperformed SVM significantly (McNemar's test p = 0.0005 < 0.01) with average test accuracy of 95.0% and 92.5% respectively. The channel rank of each subject was weighted and merged using analytic hierarchical process to obtain a cross-subject ranking, which revealed the close correlation between TOVA and the visual pathway in brain