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Layered Analysis of Irregular Facades via Symmetry Maximiza Layered Analysis of Irregular Facades via Symmetry Maximiza

Layered Analysis of Irregular Facades via Symmetry Maximiza - PowerPoint Presentation

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Layered Analysis of Irregular Facades via Symmetry Maximiza - PPT Presentation

Hao Zhang Kai Xu Wei Jiang Jinjie Lin Daniel CohenOr Baoquan Chen Simon Fraser University Shenzhen Institutes of Advanced Technology National University of Defense Technology Tel Aviv University ID: 279004

sfu siat tau nudt siat sfu nudt tau symmetry decomposition layering split box cand measure selection input profile ade

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Slide1

Layered Analysis of Irregular Facades via Symmetry Maximization

Hao Zhang, Kai Xu, Wei Jiang, Jinjie Lin, Daniel Cohen-Or, Baoquan Chen

Simon Fraser University

Shenzhen Institutes of Advanced Technology

National University of Defense Technology

Tel Aviv UniversitySlide2

Façade

Rich interesting structure to analyze

SFU, SIAT, NUDT, TAUSlide3

Our goal

A high-level understanding of the structure of irregular facadesA generative modelAn explanation of how the input facade was seemingly generated

Layering

Split

Decomposition

2. Instantiation

SFU, SIAT, NUDT, TAUSlide4

Generative model

A hierarchy of decompositions

SFU, SIAT, NUDT, TAUSlide5

Generative model

Two decomposition operations: split + layering

Input

+

Two substructures

Split

SFU, SIAT, NUDT, TAUSlide6

Generative model

Input

Layering

+

Two substructures (layers)

Structure completion

Two decomposition operations: split + layering

SFU, SIAT, NUDT, TAUSlide7

More compact generative model

input

split only

8 ops.

split +

layering

4 ops.

Two decomposition operations: split + layering

SFU, SIAT, NUDT, TAUSlide8

A good generative model

Two objectivesStructural: Occam’s Razor (Simplest explanation)

min.

# ops.

SFU, SIAT, NUDT, TAUSlide9

A good generative model

Two objectivesStructural: Occam’s Razor (Simplest explanation)Perceptual: Law of Gestalt (Symmetry

maximization)The two objectives can be optimized simultaneously.

Two substructures are most symmetric!

Symmetry maximization

 decomposition terminates

the fastest

SFU, SIAT, NUDT, TAUSlide10

Symmetry-driven analysis

Symmetry maximization at each decompositionHow symmetric are the two substructures?How good is the decomposition?

SFU, SIAT, NUDT, TAUSlide11

Symmetry-driven analysis

Objective: sum of symmetry measure of all internal nodes

 

 

 

 

 

SFU, SIAT, NUDT, TAUSlide12

Related works

Structuring symmetry

Folding mesh

[

Simari et al. 06]

Structuring 3D

Geometry

[Martinet 2007]

Symmetry hierarchy[Wang et al. 2007]SFU, SIAT, NUDT, TAUSlide13

Related works

Façade analysisSymmetry-summarization[Wu et al. 2011]Shape grammar

parsing[Teboul et al. 2011]

Adaptive Partitioning

[Shen et al. 2011]

Instant

architecture

[

Wonka

et al. 2003]

Layering has so far not been considered.

SFU, SIAT, NUDT, TAUSlide14

Related works

Inverse procedural modelingPartial symmetry and inverse procedural modeling[Bokeloh et al. 2010]

Inverse L-system[Stava et al. 2010]

We do not produce a shape grammar.

SFU, SIAT, NUDT, TAUSlide15

Overview – Key components

Box

abstraction

Element

groups

Candidate

selection

Hierarchy

optimization

SFU, SIAT, NUDT, TAUSlide16

Interactive box abstraction

SFU, SIAT, NUDT, TAUSlide17

Element groups

A set of well-aligned boxes whose content repeats

Must be maximal: not contained by any other one

SFU, SIAT, NUDT, TAUSlide18

Candidate decomposition selection

Split

cand

. 1

Split

cand

.

2

Layering

cand

. 1

Layering

cand

. 2

Input

Given a box pattern, find all candidates of split and

layering

SFU, SIAT, NUDT, TAUSlide19

Candidate decomposition selection

Principle 1: An element group can not divided into two components by a valid decompositionSome examples …SFU, SIAT, NUDT, TAUSlide20

Candidate decomposition selection

ExamplesInvalid split

Becomes valid after layering

SFU, SIAT, NUDT, TAUSlide21

Candidate decomposition selection

ExamplesInvalid splitBecomes valid after split

SFU, SIAT, NUDT, TAUSlide22

Candidate decomposition selection

ExamplesInvalid layeringBecomes valid after layering

SFU, SIAT, NUDT, TAUSlide23

Candidate decomposition selection

Principle 2: Candidate selection is carried out recursivelyCombinatorial search!

Split

cand

. 1

Split

cand

.

2

Layering

cand

. 1

Layering

cand

. 2

Layering

cand

. 1

Split

cand

. 1

Input

Substructure

SFU, SIAT, NUDT, TAUSlide24

Finding the optimal hierarchy

Genetic algorithm with tree representationSample and evolve population of hierarchiesGenetic operators:

Altering decomposition

Crossover

Split

Layering

Swapping sub-trees

Mutation

SFU, SIAT, NUDT, TAUSlide25

Finding the optimal hierarchy: Genetic algorithm

Fitness function:

Symmetry measure of a node (a substructure)

 

 

 

 

 

SFU, SIAT, NUDT, TAUSlide26

Symmetry measure at a node

Requirements:Continuous measure for a discrete box patternBehaves well at both ends of the symmetry spectrumIntegral Symmetry (IS):Integral of

symmetry profiles along two directions

X

Y

Perfectly symmetric

asymmetric

SFU, SIAT, NUDT, TAUSlide27

Symmetry measure of a discrete pattern

Symmetry profile – Intra-box profile

 

 

 

 

 

SFU, SIAT, NUDT, TAUSlide28

Symmetry measure of a discrete pattern

Symmetry profile – Intra-box profile

 

 

 

 

 

SFU, SIAT, NUDT, TAUSlide29

Symmetry measure of a discrete pattern

Symmetry profile – Intra-box profile

 

 

 

 

SFU, SIAT, NUDT, TAUSlide30

Symmetry measure of a discrete pattern

Symmetry profile – Inter-box profile

 

 

 

 

 

SFU, SIAT, NUDT, TAUSlide31

Symmetry measure of a discrete pattern

Combining inter-box and intra-box profiles:

Integral Symmetry

SFU, SIAT, NUDT, TAUSlide32

An application – Façade retargeting

Top-down propagation

SFU, SIAT, NUDT, TAUSlide33

An application – Façade retargeting

Top-down propagation

SFU, SIAT, NUDT, TAUSlide34

An application – Façade retargeting

Top-down propagation

SFU, SIAT, NUDT, TAUSlide35

An application – Façade retargeting

Top-down propagation

input

retargeted

SFU, SIAT, NUDT, TAUSlide36

Structure-aware façade retargeting

SFU, SIAT, NUDT, TAUSlide37

Input

Seam carving

Structure-aware

User interactive structural analysis [Lin et al. 2011]

SFU, SIAT, NUDT, TAUSlide38

Evaluation I: Integral symmetry

Symmetry ranking tests

A

B

SFU, SIAT, NUDT, TAUSlide39

Evaluation I: Integral symmetry

The accuracy score obtained is 88%Consistent with human perceptionSFU, SIAT, NUDT, TAUSlide40

Evaluation II: Symmetry-driven decomposition

 

 

max.

Our

method

SFU, SIAT, NUDT, TAUSlide41

Evaluation II: Symmetry-driven decomposition

Compare to two alternatives

Global

reflectional

symmetry

Alternative 1:

Graph-cut segmentation

Alternative 2:

SFU, SIAT, NUDT, TAUSlide42

Evaluation II: Symmetry-driven decomposition

Please select

which one, A or B, appears to

offer

the best high-level explanation of the facade structure:

SFU, SIAT, NUDT, TAUSlide43

Evaluation II: Symmetry-driven decomposition

On 600 questionsObtain a winning percentageof 73% against Alternative 1of 79% against Alternative 2SFU, SIAT, NUDT, TAUSlide44

Limitations

Box abstraction and element grouping carried out with user assistanceLimited to axis-aligned structuresLimited to binary decompositionsHuman perception relatedlearning/crowdsourcing?

SFU, SIAT, NUDT, TAUSlide45

Conclusion

Hierarchical and layered analysis of irregular facadesGenerative model: hierarchy of decompositionsA clearly defined objective: symmetry maximizationApplications:Structure-aware façade retargeting/editing/explorationSFU, SIAT, NUDT, TAUSlide46

Acknowledgement

Anonymous reviewersYangyan Li, Niloy Mitra, and Ariel ShamirParticipants of our user studiesResearch grantsNSERC Canada, NSFC China, Guangdong Sci. and Tech.

Program, Shenzhen Sci. and Inno. Program, CPSF, and the Israel Science Foundation.

SFU, SIAT, NUDT, TAUSlide47

Thank you!

Code and data are available:

kevinkaixu.net

SFU, SIAT, NUDT, TAU