Joe Marks

Design galleries: a general approach to setting parameters for computer graphics and animation

Image rendering maps scene parameters to output pixel values; animation maps motion-control parameters to trajectory values. Because these mapping functions are usually multidimensional, nonlinear, and discontinuous, finding input parameters that yield desirable output values is often a painful process of manual tweaking. Interactive evolution and inverse design are two general methodologies for computer-assisted parameter setting in which the computer plays a prominent role. In this paper we present another such methodology. Design GalleryTM (DG) interfaces present the user with the broadest selection, automatically generated and organized, of perceptually different graphics or animations that can be produced by varying a given input-parameter vector. The principal technical challenges posed by the DG approach are dispersion, finding a set of input-parameter vectors that optimally disperses the resulting output-value vectors, and arrangement, organizing the resulting graphics for easy and intuitive browsing by the user. We describe the use of DG interfaces for several parameter-setting problems: light selection and placement for image rendering, both standard and image-based; opacity and color transfer-function specification for volume rendering; and motion control for particle-system and articulated-figure animation. CR Categories: I.2.6 [Artificial Intelligence]: Problem Solving, Control Methods and Search—heuristic methods; I.3.6 [Computer Graphics]: Methodology and Techniques—interaction techniques; I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism.

Spacetime constraints revisited

The Spacetime Constraints (SC) paradigm, whereby the animator specifies what an animated figure should do but not how to do it, is a very appealing approach to animation. However, the algorithms available for realizing the SC approach are limited. Current techniques are local in nature: they all use some kind of perturbational analysis to refine an initial trajectory. We propose a global search algorithm that is capable of generating multiple novel trajectories for SC problems from scratch. The key elements of our search strategy are a method for encoding trajectories as behaviors, and a genetic search algorithm for choosing behavior parameters that is currently implemented on a massively parallel computer. We describe the algorithm and show computed solutions to SC problems for 2D articulated figures. CR Categories: I.2.6 [Artificial Intelligence]: Learning— parameter learning. I.2.6 [Artificial Intelligence]: Problem Solving, Control Methods and Search—heuristic methods. I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism— animation. I.6.3 [Simulation and Modeling]: Applications. Additional

Tangible interaction + graphical interpretation: a new approach to 3D modeling

Construction toys are a superb medium for geometric models. We argue that such toys, suitably instrumented or sensed, could be the inspiration for a new generation of easy-to-use, tangible modeling systems—especially if the tangible modeling is combined with graphical-interpretation techniques for enhancing nascent models automatically. The three key technologies needed to realize this idea are embedded computation, vision-based acquisition, and graphical interpretation. We sample these technologies in the context of two novel modeling systems: physical building blocks that self-describe, interpret, and decorate the structures into which they are assembled; and a system for scanning, interpreting, and animating clay figures.

A General Cartographic Labeling Algorithm

Some apparently powerful algorithms for automatic label placement on maps use heuristics that capture considerable cartographic expertise but are hampered by provably inefficient methods of search and optimization. On the other hand, no approach to label placement that is based on an efficient optimization technique has been applied to the production of general cartographic maps—those with labelled point, line, and area features—and shown to generate labellings of acceptable quality. We present an algorithm for label placement that achieves the twin goals of practical efficiency and high labelling quality by combining simple cartographic heuristics with effective stochastic optimization techniques.

Exhaustive approaches to 2D rectangular perfect packings

In this paper, we consider the two-dimensional rectangular strip packing problem, in the case where there is a perfect packing; that is, there is no wasted space. One can think of the problem as a jigsaw puzzle with oriented rectangular pieces. Although this comprises a quite special case for strip packing, we have found it useful as a subroutine in related work. We demonstrate a simple pruning approach that makes a branch-and-bound-based exhaustive search extremely effective for problems with less than 30 rectangles.

Automating the layout of network diagrams with specified visual organization

Network diagrams are a familiar graphic form that can express many different kinds of information. The problem of automating network-diagram layout has therefore received much attention. Previous research on network-diagram layout has focused on the problem of aesthetically optimal layout, using such criteria as the number of link crossings, the sum of all link lengths, and total diagram area. In this paper the authors propose a restatement of the network-diagram layout problem in which layout-aesthetic concerns are subordinated to perceptual-organization concerns. The authors present a notation for describing the visual organization of a network diagram. This notation is used in reformulating the layout task as a constrained-optimization problem in which constraints are derived from a visual-organization specification and optimality criteria are derived from layout-aesthetic considerations. Two new heuristic algorithms are presented for this version of the layout problem: one algorithm uses a rule-based strategy for computing a layout; the other is a massively parallel genetic algorithm. The authors demonstrate the capabilities of the two algorithms by testing them on a variety of network-diagram layout problems. >

New heuristic and interactive approaches to 2D rectangular strip packing

In this paper, we consider the two-dimensional rectangular strip packing problem. A standard simple heuristic, Bottom-Left-Decreasing (BLD), has been shown to perform quite well in practice. We introduce and demonstrate the effectiveness of BLD*, a stochastic search variation of BLD. While BLD places the rectangles in decreasing order of height, width, area, and perimeter, BLD* successively tries random orderings, chosen from a distribution determined by their Kendall-tau distance from one of these fixed orderings. Our experiments on benchmark problems show that BLD* produces significantly better packings than BLD after only 1 min of computation. Furthermore, we also show that BLD* outperforms recently reported metaheuristics. Furthermore, we observe that people seem able to reason about packing problems extremely well. We incorporate our new algorithms in an interactive system that combines the advantages of computer speed and human reasoning. Using the interactive system, we are able to quickly produce significantly better solutions than BLD* by itself.

Building virtual structures with physical blocks

We describe a tangible interface for building virtual structures using physical building blocks. We demonstrate two applications of our system. In one version, the blocks are used to construct geometric models of objects and structures for a popular game, Quake II™. In another version, buildings created with our blocks are rendered in different styles, using intelligent decoration of the building model.

Further experience with controller-based automatic motion synthesis for articulated figures

We extend an earlier automatic motion-synthesis algorithm for physically realistic articulated figures in several ways. First, we summarize several incremental improvements to the original algorithm that improve its efficiency significantly and provide the user with some ability to influence what motions are generated. These techniques can be used by an animator to achieve a desired movement style, or they can be used to guarantee variety in the motions synthesized over several runs of the algorithm. Second, we report on new mechanisms that support the concatenation of existing, automatically generated motion controllers to produce complex, composite movement. Finally, we describe initial work on generalizing the techniques from 2D to 3D articulated figures. Taken together, these results illustrate the promise and challenges afforded by the controller-based approach to automatic motion synthesis for computer animation.

Automatic motion synthesis for 3D mass-spring models

We describe how to automatically synthesize motion controllers for locomotive tasks involving animated characters modeled as 3D mass-spring lattices. The motion controllers determine an actuation sequence based on elapsed time, not physical state; actuation is represented economically using a canonical set of global lattice deformations; and stochastic search is used to determine effective values for the controller parameters. Our algorithm generates controllers that produce stylistic, visually plausible motion for simple locomotive tasks in under an hour on a standard workstation, which is more than an order of magnitude faster than comparable approaches to motion synthesis for 3D articulated-linkage models.