Estimation of environmental lighting from human face for illumination of augmented reality scenes

In this thesis, we propose a method to solve a common problem in augmented reality domain; estimating light sources in an outdoor scene and lighting virtual objects accordingly. As a basis of our method we developed a framework based on estimation of environmental lighting from well defined objects, specifically human faces. The method is tuned for outdoor use, and the algorithm is further enhanced to illuminate virtual objects exposed to direct sunlight. In the first part of this thesis, we propose a novel lighting estimation technique where we assume a user is looking straight to mobile devices camera. This technique extracts information from input images to calculate possible light sources to pass to the rendering stage. In the second part of this thesis, we propose a lighting model which uses the output from our lighting estimation in order to make objects appear as they are lit correctly by the sun light. This model uses a mathematical technique called Spherical Harmonics Lighting for real-time realistic rendering

A Comparison Study of Multi-Objective Metaheuristic Techniques for Continuous Review Stochastic Inventory System

Supply chain management which involves managing the flow of material andinformation from sources to customers has been one of the most challenging issuesfacing both the academicians and the practitioners for years. Inventory control is acrucial part of tactical decision level affecting the performance of supply chain indistribution and production. The main focus of this study is to compare theperformance of different multi-objective metaheuristic techniques to optimizeinventory parameters for single-product continuous review stochastic inventorysystem with transportation costs. The simulation-based optimization method is usedto solve the problem by combining the simulation model and metaheuristicalgorithms in order to determine the inventory policy taking into account twoconflicting objectives: customer service level and total inventory cost. We build adiscrete event simulation model to evaluate the objective function of the problem.The Metaheuristic techniques such as the genetic algorithm and particle swarmoptimization are applied to search the solution space. The results obtained by allthese proposed techniques are compared and the effectiveness of each technique hasbeen illustrated

MEMS 411: Soccer Robot Project

This project aims at designing a robot that is capable of playing a simplified form of soccer against other robots. The original competition was created by the ASME organization as a student design competition in 2018. This project is an adapted version in which some of the rules and guidelines have been changed to fit the goals of this class better. The design parameters for this project include: having the robot drive around the parameter of the playing field in under 17 seconds, having the vehicle successfully capture the ball within 2 seconds of approaching 8 out of times, and having the vehicle make more than out of shots from the mid-line of the field with having the robot approach from the sideline with the ball placed in the center

Synthesis and Thermal Characterization of p-Coumaric Acid Complexes of CoII, NiII, CuII and ZnII Metal Cations and Biological Applications

T he phenolic compound used in this study is p-coumaric acid, which is the derivative of phenolic acid playing a role in giving color, odor and taste to the plants. The p-coumaric acid is an organic compound derived from cinnamic acid. There are three isomers of this structure as ortho-, meta- and para- depending on the location of the hydroxyl group within the structure. In this study, metal complexes of p-coumaric acid ligand with the transition metal cations CoII, NiII, CuII, ZnII were synthesized. The structure of the synthesized complexes was studied via elemental analysis, infrared and ultraviolet-visible spectroscopy, magnetic measurements, melting point and thermal analysis. Furthermore the biological properties of these new molecules were studie

Statistically segregated k-space sampling for accelerating multiple-acquisition MRI

A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techniques can alleviate this limitation via randomly undersampled acquisitions. A frequent sampling strategy is to prescribe for each acquisition a different random pattern drawn from a common sampling density. However, naive random patterns often contain gaps or clusters across the acquisition dimension that in turn can degrade reconstruction quality or reduce scan efficiency. To address this problem, a statistically-segregated sampling method is proposed for multiple-acquisition MRI. This method generates multiple patterns sequentially, while adaptively modifying the sampling density to minimize k-space overlap across patterns. As a result, it improves incoherence across acquisitions while still maintaining similar sampling density across the radial dimension of k-space. Comprehensive simulations and in vivo results are presented for phase-cycled balanced steady-state free precession and multi-echo T2-weighted imaging. Segregated sampling achieves significantly improved quality in both Fourier and compressedsensing reconstructions of multiple-acquisition datasets

Estimation of environmental lighting from known geometries for mobile augmented reality

Light source estimation and virtual lighting must be believable in terms of appearance and correctness in augmented reality scenes. As a result of illumination complexity in an outdoor scene, realistic lighting for augmented reality is still a challenging problem. In this paper, we propose a framework based on an estimation of environmental lighting from well-defined objects, specifically human faces. The method is tuned for outdoor use, and the algorithm is further enhanced to illuminate virtual objects exposed to direct sunlight. Our model can be integrated into existing mobile augmented reality frameworks to enhance visual perception

Light source estimation in mobile augmented reality scenes by using human face geometry

Light source estimation and virtual lighting must be believable in terms of appearance and correctness in augmented reality scenes. As a result of illumination complexity in an outdoor scene, realistic lighting for augmented reality is still a challenging problem. In this paper, we propose a framework based on an estimation of environmental lighting from well-defined objects, specifically human faces. The method is tuned for outdoor use, and the algorithm is further enhanced to illuminate virtual objects exposed to direct sunlight. Our model can be integrated into existing mobile augmented reality frameworks to enhance visual perception

Computational Sciences and

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