Yotam I. Gingold

Computing discrete shape operators on general meshes

Discrete curvature and shape operators, which capture complete information about directional curvatures at a point, are essential in a variety of applications: simulation of deformable two‐dimensional objects, variational modeling and geometric data processing. In many of these applications, objects are represented by meshes. Currently, a spectrum of approaches for formulating curvature operators for meshes exists, ranging from highly accurate but computationally expensive methods used in engineering applications to efficient but less accurate techniques popular in simulation for computer graphics.

A direct texture placement and editing interface

The creation of most models used in computer animation and computer games requires the assignment of texture coordinates, texture painting, and texture editing. We present a novel approach for texture placement and editing based on direct manipulation of textures on the surface. Compared to conventional tools for surface texturing, our system combines UV-coordinate specification and texture editing into one seamless process, reducing the need for careful initial design of parameterization and providing a natural interface for working with textures directly on 3D surfaces.A combination of efficient techniques for interactive constrained parameterization and advanced input devices makes it possible to realize a set of natural interaction paradigms. The texture is regarded as a piece of stretchable material, which the user can position and deform on the surface, selecting arbitrary sets of constraints and mapping texture points to the surface; in addition, the multi-touch input makes it possible to specify natural handles for texture manipulation using point constraints associated with different fingers. Pressure can be used as a direct interface for texture combination operations. The 3D position of the object and its texture can be manipulated simultaneously using two-hand input.

Topology-based smoothing of 2D scalar fields with C1-continuity

Data sets coming from simulations or sampling of real‐world phenomena often contain noise that hinders their processing and analysis. Automatic filtering and denoising can be challenging: when the nature of the noise is unknown, it is difficult to distinguish between noise and actual data features; in addition, the filtering process itself may introduce “artificial” features into the data set that were not originally present. In this paper, we propose a smoothing method for 2D scalar fields that gives the user explicit control over the data features. We define features as critical points of the given scalar function, and the topological structure they induce (i.e., the Morse‐Smale complex). Feature significance is rated according to topological persistence. Our method allows filtering out spurious features that arise due to noise by means of topological simplification, providing the user with a simple interface that defines the significance threshold, coupled with immediate visual feedback of the remaining data features. In contrast to previous work, our smoothing method guarantees a C1‐continuous output scalar field with the exact specified features and topological structures.

Micro perceptual human computation for visual tasks

Human Computation (HC) utilizes humans to solve problems or carry out tasks that are hard for pure computational algorithms. Many graphics and vision problems have such tasks. Previous HC approaches mainly focus on generating data in batch, to gather benchmarks, or perform surveys demanding nontrivial interactions. We advocate a tighter integration of human computation into online, interactive algorithms. We aim to distill the differences between humans and computers and maximize the advantages of both in one algorithm. Our key idea is to decompose such a problem into a massive number of very simple, carefully designed, human micro-tasks that are based on perception, and whose answers can be combined algorithmically to solve the original problem. Our approach is inspired by previous work on micro-tasks and perception experiments. We present three specific examples for the design of micro perceptual human computation algorithms to extract depth layers and image normals from a single photograph, and to augment an image with high-level semantic information such as symmetry.

Shading-based surface editing

We present a system for free-form surface modeling that allows a user to modify a shape by changing its rendered, shaded image using stroke-based drawing tools. User input is translated into a set of tangent and positional constraints on the surface. A new shape, whose rendered image closely approximates user input, is computed using an efficient and stable surface optimization procedure. We demonstrate how several types of free-form surface edits which may be difficult to cast in terms of standard deformation approaches can be easily performed using our system.

Pixelated image abstraction

We present an automatic method that can be used to abstract high resolution images into very low resolution outputs with reduced color palettes in the style of pixel art. Our method simultaneously solves for a mapping of features and a reduced palette needed to construct the output image. The results are an approximation to the results generated by pixel artists. We compare our method against the results of a naive process common to image manipulation programs, as well as the hand-crafted work of pixel artists. Through a formal user study and interviews with expert pixel artists we show that our results offer an improvement over the naive methods.

RigMesh: automatic rigging for part-based shape modeling and deformation

The creation of a 3D model is only the first stage of the 3D character animation pipeline. Once a model has been created, and before it can be animated, it must be rigged. Manual rigging is laborious, and automatic rigging approaches are far from real-time and do not allow for incremental updates. This is a hindrance in the real world, where the shape of a model is often revised after rigging has been performed. In this paper, we introduce algorithms and a user-interface for sketch-based 3D modeling that unify the modeling and rigging stages of the 3D character animation pipeline. Our algorithms create a rig for each sketched part in real-time, and update the rig as parts are merged or cut. As a result, users can freely pose and animate their shapes and characters while rapidly iterating on the base shape. The rigs are compatible with the state-of-the-art character animation pipeline; they consist of a low-dimensional skeleton along with skin weights identifying the surface with bones of the skeleton.

Sketch-based modeling

Sketching is one of the most natural ways to exchange ideas. It has been used by human beings since prehistory. Research has shown that human beings have an inherent ability to understand sketches. This is why sketch-based interfaces for 3D modeling are so appealing; creating and animating 3D shapes could become as simple as drawing with a tablet and a digital pen. The purpose of this tutorial is to explore the most important aspects of sketch-based modeling, from the preprocessing of sketch strokes to the problem of 3D reconstruction. We will first explain some aspects of how humans interpret sketches. The second part of the tutorial will be dedicated to the problem of filtering and processing strokes. Other parts of the tutorial will focus on the sketch-based modeling of curves and surfaces using multi-view and single-view sketches. Sketch-based modeling using prior-knowledge will be also discussed; this class of methods is particularly well adapted to the 3D reconstruction of complex shapes. The last part of the tutorial addresses sketch-based interfaces for editing 3D shapes.

Shape optimization using reflection lines

Many common objects have highly reflective metallic or painted finishes. Their appearance is primarily defined by the distortion the curved shape of the surface introduces in the reflections of surrounding objects. Reflection lines are commonly used for surface interrogation, as they capture many essential aspects of reflection distortion directly, and clearly show surface imperfections that may be hard to see with conventional lighting. In this paper, we propose the use of functionals based on reflection lines for mesh optimization and editing. We describe a simple and efficient discretization of such functionals based on screen-space surface parameterization, and we demonstrate how such discrete functionals can be used for several types of surface editing operations.

Color Me Noisy: Example-based Rendering of Hand-colored Animations with Temporal Noise Control

We present an example‐based approach to rendering hand‐colored animations which delivers visual richness comparable to real artwork while enabling control over the amount of perceived temporal noise. This is important both for artistic purposes and viewing comfort, but is tedious or even intractable to achieve manually. We analyse typical features of real hand‐colored animations and propose an algorithm that tries to mimic them using only static examples of drawing media. We apply the algorithm to various animations using different drawing media and compare the quality of synthetic results with real artwork. To verify our method perceptually, we conducted experiments confirming that our method delivers distinguishable noise levels and reduces eye strain. Finally, we demonstrate the capabilities of our method to mask imperfections such as shower‐door artifacts.