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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22860

Title: Representations and Algorithms for Interactive Relighting
Authors: Michiels, Nick
Advisors: Bekaert, Philippe
Issue Date: 2016
Abstract: Classic relighting applications are striving to unite the virtual world and the real world by applying computer graphics algorithms to pixel and image-based descriptions. This has allowed them to apply new virtual lighting conditions on real images as well as inserting virtual objects in real environments under credible lighting conditions. However, state-of-the-art representations for geometry, materials and lighting often limit the capabilities and quality of the simulation of light in relighting applications. Spherical harmonics allow for a fast simulation of light, but can only handle low-frequency lighting effects efficiently. In addition, other relighting applications rely on Haar wavelets; which are capable of representing high-frequency lighting information as well as having great compression performance. In theory, Haar wavelets have an efficient forward rendering evaluation method. However, in practice, they need a complex rotation operator and the three factors of the rendering equation can not be constructed dynamically. In addition, they lack smoothness, which is essential for relighting applications. To overcome most of these constraints, this dissertation researched other, possibly better, representations. This dissertation introduces two new underlying basis representations designed to improve cutting edge relighting algorithms. First, we will introduce an efficient algorithm to calculate the triple product integral binding coefficients for a heterogeneous mix of wavelet bases. As mentioned above, Haar wavelets excel at encoding piecewise constant signals, but are inadequate for compactly representing smooth signals for which high-order wavelets are ideal. Our algorithm provides an efficient way to calculate the tensor of these binding coefficients, which is essential for the correct evaluation of the light transport integral. The algorithm exploits both the hierarchical nature and vanishing moments of the wavelet bases, as well as the sparsity and symmetry of the tensor. The effectiveness of high-order wavelets will be demonstrated in a rendering application. The smoother wavelets represent the signals more effectively and with less blockiness than their Haar wavelet counterpart. Using a heterogeneous mix of wavelets allows us to overcome the smoothness problem. However, wavelets still constrain one or several factors of the rendering equation, keeping them inadequate for more interactive rendering applications. For example, visibility is often precalculated and animations are not allowed; and changes in lighting are limited to a simple rotation and are not very detailed. Other techniques compromise on quality and often coarsely tabulate BRDF functions. In the second part of this dissertation, we research how spherical radial basis functions (SRBFs) can be used to overcome most of these problems. SRBFs have already been used in forward rendering, but they still do not guarantee full interactivity of the underlying factors of geometry, materials and lighting. We argue that an interactive representation of the factors is crucial and will greatly improve the flexibility and efficiency of a relighting algorithm. In order to dynamically change lighting conditions or alter scene geometry and materials, these three factors need to be converted to the SRBF representation in a fast manner. This dissertation presents a method to perform the SRBF data construction and rendering in real-time. To support dynamic high-frequency lighting, a multiscale residual transformation algorithm is applied. Area lights are detected through a peak detection algorithm. By using voxel cone tracing and a subsampling scheme, animated geometry casts soft shadows dynamically. At this point, we have two new approaches for evaluating triple product rendering integrals with fewer coefficients and an advantageous smoothness behavior. But how will they perform in actual relighting applications? We tried to answer this question in the final part of this dissertation by conducting experiments in two distinct use cases. A first use case focuses on the relighting of virtual objects with real lighting information of existing scenes. To demonstrate this, we have developed an augmented reality application. The ambition is to augment omnidirectional video, also called $360^{\circ}$ video, with natural lit virtual objects and to make the experience more realistic for users. Recent years have known a proliferation of real-time capturing and rendering methods for omnidirectional video. Together with these technologies, rendering devices such as virtual reality glasses have tried to increase the immersive experience of users. Structure-from-motion is applied to the omnidirectional video to reconstruct the trajectory of the camera. Then, the position of an inserted virtual object is linked to the appropriate 360 degree environment map. State-of-the-art augmented reality applications have often lacked realistic appearance and lighting, but our spherical radial basis rendering framework is capable of evaluating the rendering equation in real-time with fully dynamic factors. The captured omnidirectional video can be directly used as lighting information by feeding it to our renderer, where it is instantly transformed to the proper SRBF basis. We demonstrate an application in which a computer generated vehicle can be controlled through an urban environment. The second use case addresses the relighting of real objects. It will show more practical examples of how an improved representation will influence the quality and time performance of existing inverse rendering and intrinsic image decomposition applications. Such relighting techniques try to extract geometry, material and lighting information of real scenes out of one or multiple input images. First, we show how an inverse rendering technique, as introduced by Haber et al., would benefit from the smooth behavior of our high-order wavelet or SRBF representation. To allow for a hierarchical optimization algorithm, where the lower level coefficients are estimated first and then more detailed coefficients are inserted based on the well-posedness of the system, it is essential that the lower level coefficients are good approximates of the signal to estimate and thus have a smooth behavior. Besides a better refinement method, we also show how an integration with our SRBF triple product renderer will reduce the execution time of the optimization process from hours to minutes. Then, in a second application, we conduct experiments on the existing intrinsic image decomposition problem of Barron and Malik, where we used our SRBF renderer in combination with a prior based optimization method. We achieve this by adapting the SRBF rendering framework to export the proper gradients for the L-BFGS minimization step.
URI: http://hdl.handle.net/1942/22860
Category: T1
Type: Theses and Dissertations
Appears in Collections: PhD theses
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