Sparse Volumetric Deformation

Volume rendering is becoming increasingly popular as applications require realistic solid shape representations with seamless texture mapping and accurate filtering. However rendering sparse volumetric data is difficult because of the limited memory and processing capabilities of current hardware. To address these limitations, the volumetric information can be stored at progressive resolutions in the hierarchical branches of a tree structure, and sampled according to the region of interest. This means that only a partial region of the full dataset is processed, and therefore massive volumetric scenes can be rendered efficiently. The problem with this approach is that it currently only supports static scenes. This is because it is difficult to accurately deform massive amounts of volume elements and reconstruct the scene hierarchy in real-time. Another problem is that deformation operations distort the shape where more than one volume element tries to occupy the same location, and similarly gaps occur where deformation stretches the elements further than one discrete location. It is also challenging to efficiently support sophisticated deformations at hierarchical resolutions, such as character skinning or physically based animation. These types of deformation are expensive and require a control structure (for example a cage or skeleton) that maps to a set of features to accelerate the deformation process. The problems with this technique are that the varying volume hierarchy reflects different feature sizes, and manipulating the features at the original resolution is too expensive; therefore the control structure must also hierarchically capture features according to the varying volumetric resolution. This thesis investigates the area of deforming and rendering massive amounts of dynamic volumetric content. The proposed approach efficiently deforms hierarchical volume elements without introducing artifacts and supports both ray casting and rasterization renderers. This enables light transport to be modeled both accurately and efficiently with applications in the fields of real-time rendering and computer animation. Sophisticated volumetric deformation, including character animation, is also supported in real-time. This is achieved by automatically generating a control skeleton which is mapped to the varying feature resolution of the volume hierarchy. The output deformations are demonstrated in massive dynamic volumetric scenes

Improving automatic rigging for 3D humanoid characters

In the field of computer animation the process of creating an animated character is usually a long and tedious task. An animation character is usually efined by a 3D mesh (a set of triangles in the space) that gives its external appearance or shape to the character. It also used to have an inner structure, the skeleton. When a skeleton is associated to a character mesh, this association is called skeleton binding, and a skeleton bound to a character mesh is an animation rig. Rigging from scratch a character can be a very boring process. The definition and creation of a centered skeleton together with the ’painting’, by an artist,of the influence parameters between the skeleton and the mesh (the skinning) s the most demanding part to achieve an acceptable behavior for a character. This rigging process can be simplified and accelerated using an automatic rigging method. Automatic rigging methods consist in taking as input a 3D mesh, generate a skeleton based in the shape of the original model, bound the input mesh to the generated skeleton, and finally to compute a set of parameters based in a chosen skinning method. The main objective of this thesis is to generate a method for rigging a 3D arbitrary model with minimum user interaction. This can be useful to people without experience in the animation field or to experienced people to accelerate the rigging process from days to hours or minutes depending the needed quality. Having in mind this situation we have designed our method as a set of tools that can be applied to general input models defined by an artist. The contributions made in the development of this thesis can be summarized as: • Generation of an animation Rig: Having an arbitrary closed mesh we have implemented a thinning method to create first an unrefined geometry skeleton that captures the topology and pose of the input character. Using this geometric skeleton as starting point we use a refining method that creates an adjusted logic skeleton based in a template, or may be defined by the user, that is compatible with the current animation formats. The output logic skeleton is specific for each character, and it is bounded to the input mesh to create an animation rig. • Skinning: Having defined an animation rig for an arbitrary mesh we have developed an improved skinning method; this method is based on the Linear Blend Skinning(LBS) algorithm. Our contributions in the skinning field can be sub-divided in: – We propose a segmentation method that works as the core element in a weight assigning algorithm and a skinning lgorithm, we also have developed an automatic algorithm to compute the skin weights of the LBS Skinning of a rigged polygonal mesh. – Our proposed skinning algorithm uses as base the features of the LBS Skinning. The main purpose of the developed algorithm is to solve the well-known ”candy wrap” artifact; that produces a substantial loss of volume when a link of an animation skeleton is rotated over its own axis. We have compared our results with the most important methods in the skinning field, such as Dual Quaternion Skinning (DQS) and LBS, achieving a better performance over DQS and an improvement in quality over LBS. • Animation tools: We have developed a set of Autodesk Maya commands that works together as rig tool, using our previous proposed methods. • Animation loader: Moreover, an animation loader tool has been implemented, that allows the user to load animations from a skeleton with different structure to a rigged 3D model. The contributions previously described has been published in 3 research papers, the first two were presented in international congresses and the third one was acepted for its publication in an JCR indexed journal.En el campo de la animación por computadora el proceso de crear un personaje de animación es comúnmente una tarea larga y tediosa. Un personaje de animación está definido usualmente por una malla tridimensional (un conjunto de triángulos en el espacio) que le dan su apariencia externa y forma al personaje. Es igualmente común que este tenga una estructura interna, un esqueleto de animación. Cuando un esqueleto esta asociado con una malla tridimensional, a esta asociación se le llama ligado de esqueleto, y un esqueleto ligado a la mallade un personaje es conocido en inglés como "animation rig" (el conjunto de elementos necesarios, que unidos sirven para animar un personaje). Hacer el rigging desde cero de un personaje puede ser un proceso muy tedioso. La definición y creación de un esqueleto centrado en la malla junto con el "pintado" por medio de un artista de los parámetros de influencia entre el esqueleto y la malla 3D (lo que se conoce como skinning) es la parte mas demandante para alcanzar un compartimiento aceptable al deformase (moverse) la malla de un personaje. Los métodos de rigging automáticos consisten en tomar una malla tridimensional como elemento de entrada, generar un esqueleto basado en la forma del modelo original, ligar la malla de entrada al esqueleto generado y finamente calcular el conjunto de parámetros utilizados por el método de skinning elegido. El principal objetivo de esta tesis es el generar un método de rigging para un modelo tridimensional arbitrario con una interacción mínima del usuario. Este método puede ser útil para gente con poca experiencia en el campo de la animación, o para gente experimentada que quiera acelerar el proceso de rigging de días a horas o inclusive minutos, dependiendo de la calidad requerida. Teniendo en mente esta situación, hemos diseñado nuestro método como un conjunto de herramientas las cuales pueden ser aplicadas a modelos de entrada generados por cualquier artista. Las contribuciones hechas en el desarrollo de esta tesis pueden resumirse a: -Generación de un rig de animación: Teniendo una malla cerrada cualquiera, hemos implementado un método para crear primero un esqueleto geométrico sin refinar, el cual capture la pose y la topología del personaje usado como elemento de entrada. Tomando este esqueleto geométrico como punto de partida usamos un método de refinado que crea un "esqueleto lógico" adaptado a la forma del geométrico basándonos en una plantilla definida por el usuario o previamente definida, que sea compatible con los formatos actuales de animación. El esqueleto lógico generado será especifico para cada personaje, y esta ligado a la malla de entrada para así crear un rig de animación. - Skinning: Teniendo definido un rig de animación para una malla de entrada arbitraria, hemos desarrollado un método mejorado de skinning, este método sera basado en el algoritmo "Linear Blending Skinnig" (algoritmo de skinning por combinación lineal, LBS por sus siglas en inglés). Nuestras contribuciones en el campo del skinnig son: - Proponemos un nuevo método de segmentación de mallas que sea la parte medular para algoritmos de asignación automática de pesos y de skinning, también hemos desarrollado un algoritmo automático que calcule los pesos utilizados por el algoritmo LBS para una malla poligonal que tenga un rig de animación. - Nuestro algoritmo de skinning propuesto usará como base las características del algoritmo LBS. El principal propósito del algoritmo desarrollado es el solucionar el defecto conocido como "envoltura de caramelo" (candy wrapper artifact), que produce una substancial perdida de volumen al rotar una de las articulaciones del esqueleto de animación sobre su propio eje. Nuestros resultados son comparados con los métodos mas importantes en el campo del skinning tal como Cuaterniones Duales (Dual Quaternions Skinning, DQS) y LBS, alcanzando un mejor desempeño que DQS y una mejora importante sobre LBSPostprint (published version

Unwind: Interactive Fish Straightening

The ScanAllFish project is a large-scale effort to scan all the world's 33,100 known species of fishes. It has already generated thousands of volumetric CT scans of fish species which are available on open access platforms such as the Open Science Framework. To achieve a scanning rate required for a project of this magnitude, many specimens are grouped together into a single tube and scanned all at once. The resulting data contain many fish which are often bent and twisted to fit into the scanner. Our system, Unwind, is a novel interactive visualization and processing tool which extracts, unbends, and untwists volumetric images of fish with minimal user interaction. Our approach enables scientists to interactively unwarp these volumes to remove the undesired torque and bending using a piecewise-linear skeleton extracted by averaging isosurfaces of a harmonic function connecting the head and tail of each fish. The result is a volumetric dataset of a individual, straight fish in a canonical pose defined by the marine biologist expert user. We have developed Unwind in collaboration with a team of marine biologists: Our system has been deployed in their labs, and is presently being used for dataset construction, biomechanical analysis, and the generation of figures for scientific publication

Capturing Hand-Object Interaction and Reconstruction of Manipulated Objects

Hand motion capture with an RGB-D sensor gained recently a lot of research attention, however, even most recent approaches focus on the case of a single isolated hand. We focus instead on hands that interact with other hands or with a rigid or articulated object. Our framework successfully captures motion in such scenarios by combining a generative model with discriminatively trained salient points, collision detection and physics simulation to achieve a low tracking error with physically plausible poses. All components are unified in a single objective function that can be optimized with standard optimization techniques. We initially assume a-priori knowledge of the object’s shape and skeleton. In case of unknown object shape there are existing 3d reconstruction methods that capitalize on distinctive geometric or texture features. These methods though fail for textureless and highly symmetric objects like household articles, mechanical parts or toys. We show that extracting 3d hand motion for in-hand scanning e↵ectively facilitates the reconstruction of such objects and we fuse the rich additional information of hands into a 3d reconstruction pipeline. Finally, although shape reconstruction is enough for rigid objects, there is a lack of tools that build rigged models of articulated objects that deform realistically using RGB-D data. We propose a method that creates a fully rigged model consisting of a watertight mesh, embedded skeleton and skinning weights by employing a combination of deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow

Understanding the Structure of 3D Shapes

Compact representations of three dimensional objects are very often used in computer graphics to create effective ways to analyse, manipulate and transmit 3D models. Their ability to abstract from the concrete shapes and expose their structure is important in a number of applications, spanning from computer animation, to medicine, to physical simulations. This thesis will investigate new methods for the generation of compact shape representations. In the first part, the problem of computing optimal PolyCube base complexes will be considered. PolyCubes are orthogonal polyhedra used in computer graphics to map both surfaces and volumes. Their ability to resemble the original models and at the same time expose a very simple and regular structure is important in a number of applications, such as texture mapping, spline fitting and hex-meshing. The second part will focus on medial descriptors. In particular, two new algorithms for the generation of curve-skeletons will be presented. These methods are completely based on the visual appearance of the input, therefore they are independent from the type, number and quality of the primitives used to describe a shape, determining, thus, an advancement to the state of the art in the field

Understanding the Structure of 3D Shapes

Compact representations of three dimensional objects are very often used in computer graphics to create effective ways to analyse, manipulate and transmit 3D models. Their ability to abstract from the concrete shapes and expose their structure is important in a number of applications, spanning from computer animation, to medicine, to physical simulations. This thesis will investigate new methods for the generation of compact shape representations. In the first part, the problem of computing optimal PolyCube base complexes will be considered. PolyCubes are orthogonal polyhedra used in computer graphics to map both surfaces and volumes. Their ability to resemble the original models and at the same time expose a very simple and regular structure is important in a number of applications, such as texture mapping, spline fitting and hex-meshing. The second part will focus on medial descriptors. In particular, two new algorithms for the generation of curve-skeletons will be presented. These methods are completely based on the visual appearance of the input, therefore they are independent from the type, number and quality of the primitives used to describe a shape, determining, thus, an advancement to the state of the art in the field

Perception and Motion: use of Computer Vision to solve Geometry Processing problems

Computer vision and geometry processing are often see as two different and, in a certain sense, distant fields: the first one works on two-dimensional data, while the other needs three dimensional information. But are 2D and 3D data really disconnected? Think about the human vision: each eye captures patterns of light, that are then used by the brain in order to reconstruct the perception of the observed scene. In a similar way, if the eye detects a variation in the patterns of light, we are able to understand that the scene is not static; therefore, we're able to perceive the motion of one or more object in the scene. In this work, we'll show how the perception of the 2D motion can be used in order to solve two significant problems, both dealing with three-dimensional data. In the first part, we'll show how the so-called optical flow, representing the observed motion, can be used to estimate the alignment error of a set of digital cameras looking to the same object. In the second part, we'll see how the detected 2D motion of an object can be used to better understand its underlying geometric structure by means of detecting its rigid parts and the way they are connected