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Item Motion Aware Exposure Bracketing for HDR Video(The Eurographics Association and John Wiley & Sons Ltd., 2015) Gryaditskaya, Yulia; Pouli, Tania; Reinhard, Erik; Myszkowski, Karol; Seidel, Hans-Peter; Jaakko Lehtinen and Derek NowrouzezahraiMobile phones and tablets are rapidly gaining significance as omnipresent image and video capture devices. In this context we present an algorithm that allows such devices to capture high dynamic range (HDR) video. The design of the algorithm was informed by a perceptual study that assesses the relative importance of motion and dynamic range. We found that ghosting artefacts are more visually disturbing than a reduction in dynamic range, even if a comparable number of pixels is affected by each. We incorporated these findings into a real-time, adaptive metering algorithm that seamlessly adjusts its settings to take exposures that will lead to minimal visual artefacts after recombination into an HDR sequence. It is uniquely suitable for real-time selection of exposure settings. Finally, we present an off-line HDR reconstruction algorithm that is matched to the adaptive nature of our real-time metering approach.Item Modeling Luminance Perception at Absolute Threshold(The Eurographics Association and John Wiley & Sons Ltd., 2015) Kellnhofer, Petr; Ritschel, Tobias; Myszkowski, Karol; Eisemann, Elmar; Seidel, Hans-Peter; Jaakko Lehtinen and Derek NowrouzezahraiWhen human luminance perception operates close to its absolute threshold, i. e., the lowest perceivable absolute values, appearance changes substantially compared to common photopic or scotopic vision. In particular, most observers report perceiving temporally-varying noise. Two reasons are physiologically plausible; quantum noise (due to the low absolute number of photons) and spontaneous photochemical reactions. Previously, static noise with a normal distribution and no account for absolute values was combined with blue hue shift and blur to simulate scotopic appearance on a photopic display for movies and interactive applications (e.g., games). We present a computational model to reproduce the specific distribution and dynamics of ''scotopic noise'' for specific absolute values. It automatically introduces a perceptually-calibrated amount of noise for a specific luminance level and supports animated imagery. Our simulation runs in milliseconds at HD resolution using graphics hardware and favorably compares to simpler alternatives in a perceptual experiment.Item Guiding Image Manipulations using Shape-appearance Subspaces from Co-alignment of Image Collections(The Eurographics Association and John Wiley & Sons Ltd., 2015) Nguyen, Chuong H.; Nalbach, Oliver; Ritschel, Tobias; Seidel, Hans-Peter; Olga Sorkine-Hornung and Michael WimmerWe propose a system to restrict the manipulation of shape and appearance in an image to a valid subspace which we learn from a collection of exemplar images. To this end, we automatically co-align a collection of images and learn a subspace model of shape and appearance using principal components. As finding perfect image correspondences for general images is not feasible, we build an approximate partial alignment and improve bad alignments leveraging other, more successful alignments. Our system allows the user to change appearance and shape in real-time and the result is ''projected'' onto the subspace of meaningful changes. The change in appearance and shape can either be locked or performed independently. Additional applications include suggestion of alternative shapes or appearance.Item Optimal Spline Approximation via l0-Minimization(The Eurographics Association and John Wiley & Sons Ltd., 2015) Brandt, Christopher; Seidel, Hans-Peter; Hildebrandt, Klaus; Olga Sorkine-Hornung and Michael WimmerSplines are part of the standard toolbox for the approximation of functions and curves in Rd. Still, the problem of finding the spline that best approximates an input function or curve is ill-posed, since in general this yields a ''spline'' with an infinite number of segments. The problem can be regularized by adding a penalty term for the number of spline segments. We show how this idea can be formulated as an 0-regularized quadratic problem. This gives us a notion of optimal approximating splines that depend on one parameter, which weights the approximation error against the number of segments. We detail this concept for different types of splines including B-splines and composite Bézier curves. Based on the latest development in the field of sparse approximation, we devise a solver for the resulting minimization problems and show applications to spline approximation of planar and space curves and to spline conversion of motion capture data.Item LeSSS: Learned Shared Semantic Spaces for Relating Multi-Modal Representations of 3D Shapes(The Eurographics Association and John Wiley & Sons Ltd., 2015) Herzog, Robert; Mewes, Daniel; Wand, Michael; Guibas, Leonidas; Seidel, Hans-Peter; Mirela Ben-Chen and Ligang LiuIn this paper, we propose a new method for structuring multi-modal representations of shapes according to semantic relations. We learn a metric that links semantically similar objects represented in different modalities. First, 3D-shapes are associated with textual labels by learning how textual attributes are related to the observed geometry. Correlations between similar labels are captured by simultaneously embedding labels and shape descriptors into a common latent space in which an inner product corresponds to similarity. The mapping is learned robustly by optimizing a rank-based loss function under a sparseness prior for the spectrum of the matrix of all classifiers. Second, we extend this framework towards relating multi-modal representations of the geometric objects. The key idea is that weak cues from shared human labels are sufficient to obtain a consistent embedding of related objects even though their representations are not directly comparable. We evaluate our method against common base-line approaches, investigate the influence of different geometric descriptors, and demonstrate a prototypical multi-modal browser that relates 3D-objects with text, photographs, and 2D line sketches.