Robust object-based algorithms for direct shadow simulation

En informatique graphique, les algorithmes de générations d'ombres évaluent la quantité de lumière directement perçue par une environnement virtuel. Calculer précisément des ombres est cependant coûteux en temps de calcul. Dans cette dissertation, nous présentons un nouveau système basé objet robuste, qui permet de calculer des ombres réalistes sur des scènes dynamiques et ce en temps interactif. Nos contributions incluent notamment le développement de nouveaux algorithmes de génération d'ombres douces ainsi que leur mise en oeuvre efficace sur processeur graphique. Nous commençons par formaliser la problématique du calcul d'ombres directes. Tout d'abord, nous définissons ce que sont les ombres directes dans le contexte général du transport de la lumière. Nous étudions ensuite les techniques interactives qui génèrent des ombres directes. Suite à cette étude nous montrons que mêmes les algorithmes dit physiquement réalistes se reposent sur des approximations. Nous mettons également en avant, que malgré leur contraintes géométriques, les algorithmes d'ombres basées objet sont un bon point de départ pour résoudre notre problématique de génération efficace et robuste d'ombres directes. Basé sur cette observation, nous étudions alors le système basé objet existant et mettons en avant ses problèmes de robustesse. Nous proposons une nouvelle technique qui améliore la qualité des ombres générées par ce système en lui ajoutant une étape de mélange de pénombres. Malgré des propriétés et des résultats convaincants, les limitations théoriques et de mise en oeuvre limite la qualité générale et les performances de cet algorithme. Nous présentons ensuite un nouvel algorithme d'ombres basées objet. Cet algorithme combine l'efficacité de l'approche basée objet temps réel avec la précision de sa généralisation au rendu hors ligne. Notre algorithme repose sur l'évaluation locale du nombre d'objets entre deux points : la complexité de profondeur. Nous décrivons comment nous utilisons cet algorithme pour échantillonner la complexité de profondeur entre les surfaces visibles d'une scène et une source lumineuse. Nous générons ensuite des ombres à partir de cette information soit en modulant l'éclairage direct soit en intégrant numériquement l'équation d'illumination directe. Nous proposons ensuite une extension de notre algorithme afin qu'il puisse prendre en compte les ombres projetées par des objets semi-opaque. Finalement, nous présentons une mise en oeuvre efficace de notre système qui démontre que des ombres basées objet peuvent être générées de façon efficace et ce même sur une scène dynamique. En rendu temps réel, il est commun de représenter des objets très détaillés encombinant peu de triangles avec des textures qui représentent l'opacité binaire de l'objet. Les techniques de génération d'ombres basées objet ne traitent pas de tels triangles dit "perforés". De par leur nature, elles manipulent uniquement les géométries explicitement représentées par des primitives géométriques. Nous présentons une nouvel algorithme basé objet qui lève cette limitation. Nous soulignons que notre méthode peut être efficacement combinée avec les systèmes existants afin de proposer un système unifié basé objet qui génère des ombres à la fois pour des maillages classiques et des géométries perforées. La mise en oeuvre proposée montre finalement qu'une telle combinaison fournit une solution élégante, efficace et robuste à la problématique générale de l'éclairage direct et ce aussi bien pour des applications temps réel que des applications sensibles à la la précision du résultat.Direct shadow algorithms generate shadows by simulating the direct lighting interaction in a virtual environment. The main challenge with the accurate direct shadow problematic is its computational cost. In this dissertation, we develop a new robust object-based shadow framework that provides realistic shadows at interactive frame rate on dynamic scenes. Our contributions include new robust object-based soft shadow algorithms and efficient interactive implementations. We start, by formalizing the direct shadow problematic. Following the light transport problematic, we first formalize what are robust direct shadows. We then study existing interactive direct shadow techniques and outline that the real time direct shadow simulation remains an open problem. We show that even the so called physically plausible soft shadow algorithms still rely on approximations. Nevertheless we exhibit that, despite their geometric constraints, object-based approaches seems well suited when targeting accurate solutions. Starting from the previous analyze, we investigate the existing object-based shadow framework and discuss about its robustness issues. We propose a new technique that drastically improve the resulting shadow quality by improving this framework with a penumbra blending stage. We present a practical implementation of this approach. From the obtained results, we outline that, despite desirable properties, the inherent theoretical and implementation limitations reduce the overall quality and performances of the proposed algorithm. We then present a new object-based soft shadow algorithm. It merges the efficiency of the real time object-based shadows with the accuracy of its offline generalization. The proposed algorithm lies onto a new local evaluation of the number of occluders between $two$ points (\ie{} the depth complexity). We describe how we use this algorithm to sample the depth complexity between any visible receiver and the light source. From this information, we compute shadows by either modulate the direct lighting or numerically solve the direct illumination with an accuracy depending on the light sampling strategy. We then propose an extension of our algorithm in order to handle shadows cast by semi opaque occluders. We finally present an efficient implementation of this framework that demonstrates that object-based shadows can be efficiently used on complex dynamic environments. In real time rendering, it is common to represent highly detailed objects with few triangles and transmittance textures that encode their binary opacity. Object-based techniques do not handle such perforated triangles. Due to their nature, they can only evaluate the shadows cast by models whose their shape is explicitly defined by geometric primitives. We describe a new robust object-based algorithm that addresses this main limitation. We outline that this method can be efficiently combine with object-based frameworks in order to evaluate approximative shadows or simulate the direct illumination for both common meshes and perforated triangles. The proposed implementation shows that such combination provides a very strong and efficient direct lighting framework, well suited to many domains ranging from quality sensitive to performance critical applications

Effect of cooking time on physical properties of almond milk-based lemak cili api gravy

One of the crucial elements in developing or reformulating product is to maintain the quality throughout its entire shelf life. This study aims to determine the effect of different cooking time on the almond milk-based of lemak cili api gravy. Various cooking times of 5, 10, 15, 20, 25 and 30 minutes were employed to the almond milk-based lemak cili api gravy followed by determination of their effects on physical properties such as total soluble solids content, pH and colour. pH was determined by using a pH meter. Refractometer was used to evaluate the total soluble solids content of almond milk-based lemak cili api gravy. The colours were determined by using spectrophotometer which expressed as L*, a* and b* values. Results showed that almond milk-based lemak cili api gravy has constant values of total soluble solids with pH range of 5 to 6, which can be classified as low acid food. Colour analysis showed that the lightness (L*) and yellowness (b*) are significantly increased while redness (a*) decreased. In conclusion, this study shows that physical properties of almond milk-based lemak cili api gravy changes by increasing the cooking time

Partial Sum Minimization of Singular Values in Robust PCA: Algorithm and Applications

Robust Principal Component Analysis (RPCA) via rank minimization is a powerful tool for recovering underlying low-rank structure of clean data corrupted with sparse noise/outliers. In many low-level vision problems, not only it is known that the underlying structure of clean data is low-rank, but the exact rank of clean data is also known. Yet, when applying conventional rank minimization for those problems, the objective function is formulated in a way that does not fully utilize a priori target rank information about the problems. This observation motivates us to investigate whether there is a better alternative solution when using rank minimization. In this paper, instead of minimizing the nuclear norm, we propose to minimize the partial sum of singular values, which implicitly encourages the target rank constraint. Our experimental analyses show that, when the number of samples is deficient, our approach leads to a higher success rate than conventional rank minimization, while the solutions obtained by the two approaches are almost identical when the number of samples is more than sufficient. We apply our approach to various low-level vision problems, e.g. high dynamic range imaging, motion edge detection, photometric stereo, image alignment and recovery, and show that our results outperform those obtained by the conventional nuclear norm rank minimization method.Comment: Accepted in Transactions on Pattern Analysis and Machine Intelligence (TPAMI). To appea

Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery

PCA is one of the most widely used dimension reduction techniques. A related easier problem is "subspace learning" or "subspace estimation". Given relatively clean data, both are easily solved via singular value decomposition (SVD). The problem of subspace learning or PCA in the presence of outliers is called robust subspace learning or robust PCA (RPCA). For long data sequences, if one tries to use a single lower dimensional subspace to represent the data, the required subspace dimension may end up being quite large. For such data, a better model is to assume that it lies in a low-dimensional subspace that can change over time, albeit gradually. The problem of tracking such data (and the subspaces) while being robust to outliers is called robust subspace tracking (RST). This article provides a magazine-style overview of the entire field of robust subspace learning and tracking. In particular solutions for three problems are discussed in detail: RPCA via sparse+low-rank matrix decomposition (S+LR), RST via S+LR, and "robust subspace recovery (RSR)". RSR assumes that an entire data vector is either an outlier or an inlier. The S+LR formulation instead assumes that outliers occur on only a few data vector indices and hence are well modeled as sparse corruptions.Comment: To appear, IEEE Signal Processing Magazine, July 201

Feature-based tracking of multiple people for intelligent video surveillance.

Intelligent video surveillance is the process of performing surveillance task automatically by a computer vision system. It involves detecting and tracking people in the video sequence and understanding their behavior. This thesis addresses the problem of detecting and tracking multiple moving people with unknown background. We have proposed a feature-based framework for tracking, which requires feature extraction and feature matching. We have considered color, size, blob bounding box and motion information as features of people. In our feature-based tracking system, we have proposed to use Pearson correlation coefficient for matching feature-vector with temporal templates. The occlusion problem has been solved by histogram backprojection. Our tracking system is fast and free from assumptions about human structure. We have implemented our tracking system using Visual C++ and OpenCV and tested on real-world images and videos. Experimental results suggest that our tracking system achieved good accuracy and can process videos in 10-15 fps.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .A42. Source: Masters Abstracts International, Volume: 45-01, page: 0347. Thesis (M.Sc.)--University of Windsor (Canada), 2006