Sculpt and sketch interfaces for 3D modeling

几千年来，素描和雕刻一直是视觉传达的媒介。从计算的早期开始，追溯到Ivan sutherland开创性的Sketchpad系统（1963），基于草图或雕塑隐喻的界面被吹捧为3D建模的“自然”方法。在过去的二十年中，出现了许多基于草图或雕刻的3D建模系统，但将视觉想法转化为数字3D模型的中心目标仍然是正在进行的研究的肥沃领域。在过去的5年里，我的研究在成功的3D建模系统中达到了高潮：ilovessketch和Analytic 3D绘图（基于草图），Shapeshop3D和MeshMixer（基于雕塑）。这和计算机图形学的类似研究在很大程度上忽略了人类视觉感知的一个重要研究机构，即研究人类感知和理解3D形状的各种偏见和固有局限性。因此，本提案旨在通过首先尝试计算我们对3D形状感知的各种偏见，以更严格的方式探索雕刻和素描3D形状建模。例如，众所周知，当被要求从斜视中画一个立方体时，人类会将其拉长。如果没有这种偏差的模型，计算机就会错误地推断出这幅画是一个拉长的长方体。相反，如果不纠正我们的视觉偏差，一个数字立方体在我们看来就像一个被压扁的长方体。因此，拟议研究的一个重要方面将建立在先前对人类感知、形状理解、抽象和艺术美学的研究基础上，并测试和模拟与视觉感知偏差有关的各种假设。尽管存在3D输入设备和显示器，但今天使用的大部分输入设备和显示器仍然是2D的。即使有一个很好的人类感知偏差模型，从2D输入推断3D形状的模糊性也使数字3D建模成为一个独特的挑战问题。有两种方法可以解决这个基本问题：通过构建更好的推理引擎，使用3D形状的上下文和可能性模型来解决歧义(例如：分析3D绘图)或通过构建更好的界面和交互式工作流程，允许用户增加他们的2D输入并明确表达他们预期的3D形状(例如。ILoveSketch)。本研究将继续探索这两个研究方向。

Sketching and sculpting have been the medium of visual communication for millenia. Since the early days of computing, as far back as Ivan Sutherlannd's seminal Sketchpad system (1963), interfaces based on a sketch or sculpt metaphor have been touted as "natural" approaches to 3D modeling. The last two decades have seen a number of promising sketch or sculpt based 3D modeling systems but the central goal of transforming a visual idea into a digital 3D model continues to be a fertile area of ongoing research. In the past 5 years my research has culminated in successful 3D modeling systems: ILoveSketch and Analytic 3D drawing (sketch-based), Shapeshop3D and MeshMixer (sculpt-based). This and similar research in computer graphics has been largely oblivious of an important body of research in human visual perception that studies the various biases inherent limitations in human perception and understanding of 3D shape. This proposal thus intends to explore sculpting and sketching for 3D shape modeling with greater rigour by first attempting to computationally model the various biases we have in our perception of 3D shape. For example, it is well-known that when asked to draw a cube from an oblique view, humans elongate it in depth significantly. Without a model for this bias, a computer would erroneously infer the drawing to be an elongated cuboid. Conversely, a digital cube, if displayed without correcting for our visual bias, would appear to us as a squashed cuboid. A significant aspect of the proposed research will thus build upon prior research in human perception, shape understanding, abstraction and aesthetics in art and test and model various hypotheses relating to biases in visual perception. Despite the existence of 3D input devices and displays, the bulk of input devices and displays in use today continue to be 2D. Even with a good model of the biases in human perecption the ambiguities in inferring 3D shape from 2D input is what makes digital 3D modeling a uniquely challenging problem. There are two ways to address this fundamental problem: by building better inference engines that use context and likelyhood models of 3D shape to resolve ambiguities (eg. Analytic 3D drawing) or by building better interfaces and interactive workflows that allow users to augment their 2D input and explicitly express their intended 3D shape (eg. ILoveSketch). This research will continue to explore both these research directions.