Learning Blind Motion Deblurring

As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime. However, taking a quick shot frequently yields a blurry result due to unwanted camera shake during recording or moving objects in the scene. Removing these artifacts from the blurry recordings is a highly ill-posed problem as neither the sharp image nor the motion blur kernel is known. Propagating information between multiple consecutive blurry observations can help restore the desired sharp image or video. Solutions for blind deconvolution based on neural networks rely on a massive amount of ground-truth data which is hard to acquire. In this work, we propose an efficient approach to produce a significant amount of realistic training data and introduce a novel recurrent network architecture to deblur frames taking temporal information into account, which can efficiently handle arbitrary spatial and temporal input sizes. We demonstrate the versatility of our approach in a comprehensive comparison on a number of challening real-world examples.Comment: International Conference on Computer Vision (ICCV) (2017

Nutrition and health claims – call for and justification of governmental intervention from the consumers’ perspective

In December 2006 the Regulation (EC) No. 1924/2006 on the use of nutrition and health claims (NHCs) on foods was enacted in order to prevent consumer deception and to harmonise law within the EU. Against this background, this paper analyses the potential costs and benefits linked with NHCs and the necessity for governmental intervention to regulate NHCs within a theoretical and empirical framework. The theoretical investigation shows that NHCs can induce direct economic effects as well as spillover effects in the market of information. Whether those effects are beneficial or adverse depends on the truthfulness of the NHCs, and consumers’ perception and processing of such claims. As self regulatory forces of the market might not be sufficient to prevent market failure due to fraudulent claims, governmental intervention seems necessary. An analysis of the EU Regulation on NHCs reveals that this law focuses on preventing the authorisation of false or misleading claims. It is less concerned with not authorising a true and correctly understood claim. The results of the empirical analysis which is based on a standardized consumer survey reveal that the stated impact of NHCs on product perception considerably differs among consumers. While e.g. some consumers feel misled by NHCs on products with a negative nutrient profile such as candies, others point out that such claims have no impact on their product perception or even help them to make better choices. The results also indicate that the great majority of consumers is opposed to a ban of NHCs on products with a negative nutrient profile such as candies and salt.nutrition and health claims, consumer deception, information economics, market transparency, consumer protection policy, Consumer/Household Economics, Food Consumption/Nutrition/Food Safety,

Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

We present a new approach for efficient approximate nearest neighbor (ANN) search in high dimensional spaces, extending the idea of Product Quantization. We propose a two-level product and vector quantization tree that reduces the number of vector comparisons required during tree traversal. Our approach also includes a novel highly parallelizable re-ranking method for candidate vectors by efficiently reusing already computed intermediate values. Due to its small memory footprint during traversal, the method lends itself to an efficient, parallel GPU implementation. This Product Quantization Tree (PQT) approach significantly outperforms recent state of the art methods for high dimensional nearest neighbor queries on standard reference datasets. Ours is the first work that demonstrates GPU performance superior to CPU performance on high dimensional, large scale ANN problems in time-critical real-world applications, like loop-closing in videos

Low-Temperature Optical Characterization of Single CdS Nanowires

We use spatially resolved micro-PL imaging at low temperature to study optical properties of two sets of CdS nanowires grown using 20 nm and 50 nm catalysts. We find that low temperature PL of single nanowires is an ideal technique to gauge the quality of a given growth run, and moreover enables the collection of detailed spatial information on single wire electronic states.Comment: IEEE Nano 2006 Proceeding

3D Acquisition of Mirroring Objects using Striped Patterns

Objects with mirroring optical characteristics are left out of the scope of most 3D scanning methods. We present here a new automatic acquisition approach, shape-from-distortion, that focuses on that category of objects, requires only a still camera and a color monitor, and produces range scans (plus a normal and a reflectance map) of the target. Our technique consists of two steps: first, an improved environment matte is captured for the mirroring object, using the interference of patterns with different frequencies to obtain sub-pixel accuracy. Then, the matte is converted into a normal and a depth map by exploiting the self-coherence of a surface when integrating the normal map along different paths. The results show very high accuracy, capturing even smallest surface details. The acquired depth maps can be further processed using standard techniques to produce a complete 3D mesh of the object

Temperature dependent photoluminescence of single CdS nanowires

Temperature dependent photoluminescence (PL) is used to study the electronic properties of single CdS nanowires. At low temperatures, both near-band edge (NBE) photoluminescence (PL) and spatially-localized defect-related PL are observed in many nanowires. The intensity of the defect states is a sensitive tool to judge the character and structural uniformity of nanowires. As the temperature is raised, the defect states rapidly quench at varying rates leaving the NBE PL which dominates up to room temperature. All PL lines from nanowires follow closely the temperature-dependent band edge, similar to that observed in bulk CdS.Comment: 11 pages, 4 figure

Low temperature photoluminescence imaging and time-resolved spectroscopy of single CdS nanowires

Time-resolved photoluminescence (PL) and micro-PL imaging were used to study single CdS nanowires at 10 K. The low-temperature PL of all CdS nanowires exhibit spectral features near energies associated with free and bound exciton transitions, with the transition energies and emission intensities varying along the length of the nanowire. In addition, several nanowires show spatially localized PL at lower energies which are associated with morphological irregularities in the nanowires. Time-resolved PL measurements indicate that exciton recombination in all CdS nanowires is dominated by non-radiative recombination at the surface of the nanowires.Comment: 9 pages, 3 figures, to be published in Applied Physics Letter

Data Fusion of Objects Using Techniques Such as Laser Scanning, Structured Light and Photogrammetry for Cultural Heritage Applications

In this paper we present a semi-automatic 2D-3D local registration pipeline capable of coloring 3D models obtained from 3D scanners by using uncalibrated images. The proposed pipeline exploits the Structure from Motion (SfM) technique in order to reconstruct a sparse representation of the 3D object and obtain the camera parameters from image feature matches. We then coarsely register the reconstructed 3D model to the scanned one through the Scale Iterative Closest Point (SICP) algorithm. SICP provides the global scale, rotation and translation parameters, using minimal manual user intervention. In the final processing stage, a local registration refinement algorithm optimizes the color projection of the aligned photos on the 3D object removing the blurring/ghosting artefacts introduced due to small inaccuracies during the registration. The proposed pipeline is capable of handling real world cases with a range of characteristics from objects with low level geometric features to complex ones

Single view reflectance capture using multiplexed scattering and time-of-flight imaging

This paper introduces the concept of time-of-flight reflectance estimation, and demonstrates a new technique that allows a camera to rapidly acquire reflectance properties of objects from a single view-point, over relatively long distances and without encircling equipment. We measure material properties by indirectly illuminating an object by a laser source, and observing its reflected light indirectly using a time-of-flight camera. The configuration collectively acquires dense angular, but low spatial sampling, within a limited solid angle range - all from a single viewpoint. Our ultra-fast imaging approach captures space-time "streak images" that can separate out different bounces of light based on path length. Entanglements arise in the streak images mixing signals from multiple paths if they have the same total path length. We show how reflectances can be recovered by solving for a linear system of equations and assuming parametric material models; fitting to lower dimensional reflectance models enables us to disentangle measurements. We demonstrate proof-of-concept results of parametric reflectance models for homogeneous and discretized heterogeneous patches, both using simulation and experimental hardware. As compared to lengthy or highly calibrated BRDF acquisition techniques, we demonstrate a device that can rapidly, on the order of seconds, capture meaningful reflectance information. We expect hardware advances to improve the portability and speed of this device.National Science Foundation (U.S.) (Award CCF-0644175)National Science Foundation (U.S.) (Award CCF-0811680)National Science Foundation (U.S.) (Award IIS-1011919)Intel Corporation (PhD Fellowship)Alfred P. Sloan Foundation (Research Fellowship