3-1 Suggestive Interface

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Из курса от партнера The University of Tokyo

Interactive Computer Graphics

161 оценки

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The University of Tokyo

Interactive Computer Graphics

161 оценки

Computer graphics can be a powerful tool for supporting visual problem solving, and interactivity plays a central role in harnessing the users' creativity. This course will introduce various interactive tools developed in computer graphics research field with their design rationales and algorithms. Examples include enhancements to graphical user interfaces, authoring tools for 2D drawings and 3D animations, and interactive computer-aided design systems. Rich live demonstrations and course assignments will give you insights and skills to design and implement such tools for your own problems.

Из урока

3D Geometric Modeling

In this module, we rise up from 2D plane to 3D space, and discuss 3D geometric modeling methods. Topics introduced are; suggestive interface for architectural models, a sketch-based modeling system for freeform shapes, a curve-based shape control method, a flower modeling system, and volumetric texture. You will see how 3D objects can be easily and quickly modeled by specially-designed 2D user interfaces!

3-1 Suggestive Interface9:24

3-2 Sketch-based Modeling14:33

3-3 Shape Control by Curves9:51

3-4 Flower Modeling10:01

3-5 Volumetric Textures11:29

Познакомьтесь с преподавателями

Takeo Igarashi
Professor
Department of Computer Science, Graduate School of Information Science and Technology

[SOUND] Hi, this is Interactive

Computer Graphics, week three.

The topic we discuss here is 3D geometric modeling.

So the challenge behind this is user interface is still mostly two-dimensional.

So, the question is how to compliment in missing information?

So, mainly depths here.

So use [UNKNOWN] 2D and how to get 3D from 2D.

There's lots of problem with our progress here.

Our solution, in general, is a user

interface, an automatic inference leveraging domain specific knowledge.

So if you do not know what you do, it's almost impossible to infer dips, but if

you know what you want to do, if you

limit the domain and you can get reasonable results.

That's the basic idea behind the works I will introduce here.

And here are the topics that we will discuss in this week.

So first one is suggestive user interface for modeling of architectural models.

And then there's sketch-based modeling of larger and stuffed things.

And then we discuss shape control by curves,

and then flower modeling, and then volumetric texture synthesis.

The first one is suggestive interface.

So, the work was published as Chateau, a suggestive interface for 3D modeling.

The motivation is here.

So current graphical user interface is dominated through

these many buttons, menus, and even more, nested menus.

It's very hard to find design command [UNKNOWN].

[UNKNOWN] About

the operation on what

you want to do on the main screen, the main field.

So if we were working on 3D modeling and if you want to do related to these three

elements in the scene you can just highlight these

three, which hints the computer to infer the request.

And then computer looks at the hints,

and then provides proposal, for the data operations.

In this case, the system proposes a box, and those are our two possibilities.

So, in other words, review the first given arguments

for the command, and then system automatically infer the command.

So let me show you a demo.

So here is a three-dimensional modeling system with a 3D

space inside, and then you can sketch lines in this way.

But here, instead of using many commands on the menu.

We simply allow the user to highlight lines.

And then, for these highlights or hints, system pro, pro presents some suggestions.

Well, why is drawing a plane and another is

drawing triangle, the other is drawing a left angle.

And you can also ignore them and then create more.

And then given the in-sweep of [UNKNOWN] lines, system

predicts, or suggests to make a rectangle, a box.

And then, again, if you do a line here,

then given this hint, system suggests to cut a box.

You can also go back and then add more lines.

And then given this hint, system suggests to cut a corner.

So in this way, user provides the hints

to the system and then the system presents suggestions.

So, this way, user does not really quiet the space [UNKNOWN] one, in the

huge command [UNKNOWN], And then you can forecast the visual content of the task.

And if you highlight this, then the system predicts, or suggests

drawing plane, and the user draws for example rectangle, triangle here.

And if you highlight these three, system suggests to make a face inside.

And then if you highlight one more, the system suggests extrusion.

And one interesting operation is like this one.

If you highlight these two and also one line here, about a third.

And this is, it was exactly dividing to the three.

We use again also the line somewhere here, and this is [UNKNOWN] divided into four.

So in this way a user can generate

this kind of diagram just by, computing operations.

[BLANK_AUDIO]

And after some time operations, you can get these kinds of results.

And this kind of operation is very useful for

repetitions, and also some symmetric structures and so on.

Now, let me describe, briefly describe, the implementation behind the, system.

So, this is the input scene.

So highlighted elements and then no highlighted elements.

So, taking this example input scene then

system is equipped with multiple suggestion engines,

they kind of parallel engines working independently

and then each engine consists of two parts.

One is examination part and one other is generator.

And the examiner examines the scene, and then

tests whether the scene matches with expected rule.

And then if it passes examination, and

then the generator generates the resulting scene.

So this is a very hardcoded program, program module provided the programmer.

But they all works in parallel.

And then specific engine and the act of specific input configuration.

And here's our list of suggestion engines.

We input method in this application.

One is [UNKNOWN] given a hint.

System generator [UNKNOWN] passing through the hint.

And also if you highlight closed roof, it suggest polygon, perpendicular two lines

suggest rectangle, [UNKNOWN] suggest a box,

and system suggest extrusion and pyramid shape.

Now these are resizing and bridges, connecting two,

two polygons and the extrusion and this is a cutting out

and also corner cutting and trimming and intersection,

duplication, repetition, mirror image and so on.

And the philosophy or concept is defined as this.

Standard user interface is like this.

So the user provides very explicit command

or very explicit instruction to the computer.

And then the computer just blindly, simply follows the instruction.

However, what we provide is more friendly, human to human like interactions.

So the user is working on the visual task directly, and then computer

implicitly observes the action and then provides help and

solution, and I think this kind of walking style can be useful.

One possible application is like this, so in your

PowerPoint or in any presentation, you have alignment show.

Alignment to is hidden somewhere in the menu, and it's not easy to find.

For example, in this PowerPoint, you can get there from some way around.

Home, and somewhere, I don't know [LAUGH] height, alignment, and somewhere.

But it's not easy to find.

However, if you highlight these four almost aligned

element, I think it's pretty reasonable, and also useful

for the system suggest particular alignment, in align

left or align center, and suggest to the user.

And if the user likes it, then it just create it, and it gets the result.

And this can be a very powerful help for the user.

So that's it and the original paper was published in 2001.

And this work, our work is strongly inspired

by a previous system called the SKETCH system.

So this SKETCH system takes two dimensional gestures and the

system will automatically generate this kind of three dimensional scene.

So what they do is very interesting.

So you input this 2D and you need to infer 3D position.

To do it the system uses a [UNKNOWN] of every

object that has to be put on top of every object.

In this way, the computer computes 3D depths and measures.

Showing multiple candidates for values to choose is also presented before,

the presented work is called Design Galleries and published in 1997.

I also recommend you to take a look at this work.

Thank you.

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