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- Miika Aittala
- The Visual Computer
- 2010

We present a practical and robust photorealistic rendering pipeline for augmented reality. We solve the real world lighting conditions from observations of a diffuse sphere or a rotated marker. The solution method is based on l 1-regularized least squares minimization, yielding a sparse set of light sources readily usable with most rendering methods. The… (More)

- Miika Aittala, Tim Weyrich, Jaakko Lehtinen
- ACM Trans. Graph.
- 2013

Spatially-varying reflectance and small geometric variations play a vital role in the appearance of real-world surfaces. Consequently, robust, automatic capture of such models is highly desirable; however, current systems require either specialized hardware, long capture times, user intervention, or rely heavily on heuristics. We describe an acquisition… (More)

- Otto Korkalo, Miika Aittala, Sanni Siltanen
- ISMAR
- 2010

In augmented reality, marker-based tracking is the most common method for camera pose estimation. Most of the markers are black and white patterns that are visually obtrusive, but they can be hidden from the video using image inpainting methods. In this paper, we present a computationally efficient approach to achieve this. We use a high-resolution hiding… (More)

- Jaakko Lehtinen, Tero Karras, Samuli Laine, Miika Aittala, Frédo Durand, Timo Aila
- ACM Trans. Graph.
- 2013

We introduce a novel Metropolis rendering algorithm that directly computes image gradients, and reconstructs the final image from the gradients by solving a Poisson equation. The reconstruction is aided by a low-fidelity approximation of the image computed during gradient sampling. As an extension of path-space Metropolis light transport, our algorithm is… (More)

- Markus Kettunen, Marco Manzi, Miika Aittala, Jaakko Lehtinen, Frédo Durand, Matthias Zwicker
- ACM Trans. Graph.
- 2015

We introduce gradient-domain rendering for Monte Carlo image synthesis. While previous gradient-domain Metropolis Light Transport sought to distribute more samples in areas of high gradients, we show, in contrast, that estimating image gradients is also possible using standard (non-Metropolis) Monte Carlo algorithms, and furthermore, that even without… (More)

- Miika Aittala, Timo Aila, Jaakko Lehtinen
- ACM Trans. Graph.
- 2016

We extend parametric texture synthesis to capture rich, spatially varying parametric reflectance models from a single image. Our input is a single head-lit flash image of a mostly flat, mostly stationary (textured) surface, and the output is a tile of SVBRDF parameters that reproduce the appearance of the material. No user intervention is required. Our key… (More)

- Miika Aittala, Tim Weyrich, Jaakko Lehtinen
- ACM Trans. Graph.
- 2015

Material appearance acquisition usually makes a trade-off between acquisition effort and richness of reflectance representation. In this paper, we instead aim for both a light-weight acquisition procedure and a rich reflectance representation simultaneously, by restricting ourselves to one, but very important, class of appearance phenomena: texture-like… (More)

Gradient-domain path tracing has recently been introduced as an efficient realistic image synthesis algorithm. This paper introduces a bidirectional gradient-domain sampler that outperforms traditional bidirectional path tracing often by a factor of two to five in terms of squared error at equal render time. It also improves over unidirectional… (More)

- Mikael Wahlström, Miika Aittala, Helinä Kotilainen, Tiina Yli-Karhu, Janne Porkka, Esa Nykänen
- Virtual Reality
- 2009

Several studies indicate that virtual reality (VR) systems are useful for end-user participation in an environmental design process. However, these systems can be costly and thus support for the decision whether to invest in a VR of some type is useful. This study presents a novel method for analysing the usefulness of a VR system for the purpose of… (More)

This document supplements the SIGGRAPH 2015 technical paper “Gradient-domain Path Tracing”. We provide additional details and steps in the derivation of a frequency analysis of gradient sampling and reconstruction for Monte Carlo integration, including a numerical experiment that we performed to validate the theory, under its simplifications. We also… (More)