This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

The demands for digital 3D content for numerous applications such as video games, movies, virtual prototyping, advertisement, virtual reality, augmented reality or even digital preservation of cultural heritage objects has led to a need for efficient and accurate automatic acquisition systems for both geometry and reflectance. This short course sheds light on the acquisition ecosystem with three of its most important components that consist in accurate acquisition methods for geometry and reflectance as well as strategies towards an efficient acquisition pipeline to fulfill the demands of industry with respect to mass digitization of 3D contents. In this context, this course provides a thorough overview of the standard methods for the acquisition of both geometry and reflectance of surfaces with different types of reflectance behavior ranging from diffuse over opaque to specular surfaces or even translucent and transparent surfaces. These standard acquisition techniques are - by design - only well-suited for a limited range of surface materials and, hence, not adequate if no prior information with respect to the surface reflectance behavior is available. For this reason, we also discuss recent advances towards an efficient, fully automatic acquisition in the scope of the concluding remarks.

Advances in geometry and reflectance acquisition (course notes)

Spatial augmented reality for product appearance design evaluation

High quality videos became an essential requirement in recent applications. High efficiency video coding (HEVC) standard provides an efficient solution for high quality videos at lower bit rates. On the other hand, HEVC comes with much higher computational cost. In particular, motion estimation (ME) in HEVC, consumes the largest amount of computations. Therefore, fast ME algorithms and hardware accelerators are proposed in order to speed-up integer ME in HEVC. This study presents a fast centre search algorithm (FCSA) and an adaptive search window algorithm (ASWA) for integer pixel ME in HEVC. In addition, centre adaptive search algorithm, a combination of the two proposed algorithms FCSA and ASWA, is proposed in order to achieve the best performance. Experimental results show notable speed-up in terms of encoding time and bit rate saving with tolerable peak signal-to-noise ratio (PSNR) quality degradation. The proposed fast search algorithms reduce the computational complexity of the HEVC encoder by 57%. This improvement is accompanied with a modest average PSNR loss of 0.014 dB and an increase by 0.6385% in terms of bit rate when compared with related works.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2015.0666

Adaptive low-complexity motion estimation algorithm for high efficiency video coding encoder

A system for reflectance acquisition of a target includes a light source, an image capture device, and a reflectance reference chart. The reflectance reference chart is fixed relative to the target. The light source provides a uniform band of light across at least a dimension of the target. The image capture device is configured and positioned to encompass at least a portion of the target and at least a portion of the reflectance reference chart within a field-of-view of the image capture device. The image capture device captures a sequence of images of the target and the reflectance reference chart during a scan thereof. Reflectance responses are calculated for the pixels in the sequence of images. Reference reflectance response distribution functions are matched to the calculated reflectance responses, and an image of the target is reconstructed based at least in part on the matched reference reflectance response distribution functions.

Obtaining spatially varying bidirectional reflectance distribution function

We present a novel high-dynamic-range (HDR) camera-based bidirectional reflectance distribution function (BRDF) measurement system that can measure the reflectance property of isotropic materials. Our developed system can measure the BRDF of highly specular materials much faster than previous systems. It measures highly dense BRDF samples for a wider reflection angle with less noise so that it provides accuracy that is necessary for computer graphics application. To estimate the reflectance of a given material, we perform an absolute photometric calibration for the HDR camera. Our system is verified by checking the Helmholtz reciprocity and comparing the performance with that of previous image-based systems. The capability and efficiency of the developed system is demonstrated by comparing the images generated by measure-and-fit and direct-rendering methods using the measured data of four different isotropic materials.

High-dynamic-range camera-based bidirectional reflectance distribution function measurement system for isotropic materials

We present a novel image-based BRDF (Bidirectional Reflectance Distribution Function) measurement system for
materials that have isotropic reflectance properties. Our proposed system is fast due to simple set up and automated
operations. It also provides a wide angular coverage and noise reduction capability so that it achieves accuracy that is
needed for computer graphics applications. We test the uniformity and constancy of the light source and the reciprocity
of the measurement system. We perform a photometric calibration of HDR (High Dynamic Range) camera to recover an
accurate radiance map from each HDR image. We verify our proposed system by comparing it with a previous imagebased
BRDF measurement system. We demonstrate the efficiency and accuracy of our proposed system by generating
photorealistic images of the measured BRDF data that include glossy blue, green plastics, gold coated metal and gold metallic paints.

A fast and accurate image-based measuring system for isotropic reflection materials

There are disclosed a system and a method for measuring reflectance of an object. The system for measuring reflectance of an object according to the present invention includes: a light source unit including a light source irradiating light to the object; a light source position adjusting unit that adjusts a position and a direction of the light source unit; a light receiving unit that acquires image data by detecting light reflected on the object; and a reflectance acquiring unit that acquires the reflectance of the object from the image data. According to the present invention, it is possible to more precisely acquire the reflectance of the object within a shorter time.

System and method for measuring reflectance of object

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High-dynamic-range camera-based bidirectional reflectance distribution function measurement system for isotropic materials

A fast and accurate image-based measuring system for isotropic reflection materials

System and method for measuring reflectance of object