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SCCG2017 Computer Simulation of Furniture Layout when Moving from One House to Another
1. Computer Simulation of Furniture Layout
when Moving from One House to Another
Takuya Yamakawa Hokkaido University
Yoshinori Dobashi Hokkaido University, UEI Research
Makoto Okabe Shizuoka University
Kei Iwasaki Wakayama University
Tsuyoshi Yamamoto Hokkaido University
1
2. Table of Contents
Introduction
Related Works
Proposed Method
Results
Conclusion and future plans
1
4. Technologies for designing every day objects
Get everyday objects that satisfy his or her particular
needs
Clothing design, interior and furniture design, architecture
design, etc.
Apply to furniture layout
Introduction
Image …
3
5. [Yu et al. 11]
[Merrell et al. 11]
Introduction
Automatic suggestion
for a single room〇
Not for Multiple rooms
⇒ Not enough for moving☓
Furniture layout design
is challenging.
Functional criterion
+
Visual criterion
Automatic furniture layout suggestion system
for Multiple rooms
4
7. Related Works
Furniture Layout Design
[Xu et al. 02] [Liu et al. 15]
For large space room [Xu et al. 02]
Using interior design guidelines and suggest a single room layout
[Merrell et al. 11]
Using crowd-sourced datasets for styles of furniture layout [Liu et al. 15]
Not dealing with designing the layout for multiple rooms
6
[Merrell et al. 11]
8. Related Works
Automatic Generation of Floor Plans
Using a Bayesian network trained on real-world floor plans
[Merrell et al. 10]
Taking into account the functionalities and the design capabilities of
buildings [Liu et al. 13]
Generating maps in games using specifically shaped blocks
(e.g. rectangular , L or T-shaped blocks ) [Liu et al. 15]
Not suggest arrangements of furniture items
[Merrell et al. 10] [Liu et al. 13] [Ma et al. 14]
7
10. Problem definition
Trouble issue to rearrange furniture items when moving into a new house.
Typically, simulating furniture layout by using printed floor plans.
No method that computes furniture layout for moving into a new house.
Trouble issue
9
11. Problem definition
HOW ?
？
New House
Trouble issue to rearrange furniture items when moving into a new house.
Typically, simulating furniture layout by using printed floor plans.
No method that computes furniture layout for moving into a new house.
Computing furniture layout for moving into a new house
Previous House
10
12. Problem definition
Similar
layout
New House
Two assumptions about how people determine the layout when moving
Relocating furniture in functionally and geometrically similar rooms in the previous house.
The layout in the new house is similar to that in the previous house.
Assign furniture items to similar function rooms and
suggest similar furniture layouts in the new house.
Previous House
11
14. 𝜙 𝐹, 𝐶 = 𝜙𝑐(𝐶)
𝑖=1
𝑁
𝜙 𝑚 𝐹𝑖 + 𝜙𝑠 𝐹𝑖
Our Approach ~ Cost Function ~
Previous House New House
1. Room
Correspondence
2. Merrell’s
Cost Function
Optimization
3. Layout
Similarity
Optimization
Cost Function
Cost Function
13
15. Cost Function
Designing a cost function that takes care of all the rooms in the
new house.
Previous House
New House 14
“Living-
Dining”
“Bedroom” “Bedroom”
“Bedroom”
“Bedroom”
“Living-
Dining”
“Bedroom”
“Bedroom”
1. Room Correspondence
16. Cost Function
Previous House
New House
Move furniture to a room in the new
house that is functionally and
geometrically similar to the room.
Designing a cost function that takes care of all the rooms in the
new house.
“Living-
Dining”
“Bedroom” “Bedroom”
“Bedroom”
“Bedroom”
“Living-
Dining”
“Bedroom”
“Bedroom” 15
1. Room Correspondence
17. Cost Function
1. Room Correspondence
Previous House
New House
𝜙 𝐶 𝑪
Taking into account the function and
area of each room to measure the quality
of the correspondence between rooms in
the previous and new house.
Move furniture to a room in the new
house that is functionally and
geometrically similar to the room.
Room Correspondence Term
Designing a cost function that takes care of all the rooms in the
new house.
16
18. Cost Function
2. Functional/Visual relationship
(Merrell et al 2011)
Previous House
New House
Design Guideline
conversation balancealignment emphasis
𝜙 𝑚 𝐹𝑖 =
𝑘
𝑤 𝑘 𝑚 𝑘(𝐹𝑖)
Taking into account the functional and
visual quality of the layout as in
Merrell’s method.𝐹𝑖
𝑚 𝑝𝑑 𝐹𝑖 , 𝑚 𝑐𝑑 𝐹𝑖 , 𝑚 𝑐𝑎 𝐹𝑖 , 𝑚 𝑣𝑏 𝐹𝑖 , 𝑚 𝑓𝑎(𝐹𝑖)
Functional/Visual term
Designing a cost function that takes care of all the rooms in the
new house.
17
19. Cost Function
3. Layout similarity
Previous House
New House
𝜙 𝑆 𝐹𝑖 =
𝑤 𝑑 𝝓 𝒅 𝑭𝒊 + 𝑤 𝜃 𝝓 𝜽(𝑭𝒊)
Measure the similarity by the positional
and orientational relationships between
furniture items.
Similarity term
Positional
Relationship
Orientational
Relationship
Designing a cost function that takes care of all the rooms in the
new house.
18
20. Optimizing the Cost Function
𝑝 𝐹, 𝐶 =
1
𝑍
exp(−𝛽𝜙 𝐹, 𝐶 )
density function
Method
𝜙 𝐹, 𝐶 = 𝜙𝑐(𝐶)
𝑖=1
𝑁
𝜙 𝑚 𝐹𝑖 + 𝜙𝑠 𝐹𝑖
Cost Function
Acceptance Probability
▶ Employ a Markov chain Monte Carlo sampler to explore
the function.
▶ Use the Metropolis-Hastings algorithm.
𝛼 𝐹 → 𝐹∗, 𝐶 = min 1,
𝑝(𝐹∗
, 𝐶)
𝑝 𝐹, 𝐶
19
21. Room Correspondence 𝜙 𝐶 𝑪
Previous House
New House
“Living-
Dining”
“Bedroom” “Bedroom”
“Bedroom”
“Bedroom”
“Living-
Dining”
“Bedroom”
“Bedroom”
Matched Labels
Previous House
New House
“Living-
Dining”
“Bedroom” “Bedroom”
“Bedroom”
“Bedroom”
“Living-
Dining”
“Bedroom”
“Bedroom”
20
Taking into account area of each room.
Make a correspondence between rooms by using room function labels.
Mismatched Labels
22. Room Correspondence 𝜙 𝐶 𝑪
Taking into account area of each room.
Make a correspondence between rooms by using room function labels.
Previous House
New House
“Living-
Dining”
“Bedroom” “Bedroom”
“Bedroom”
“Bedroom”
“Living-
Dining”
“Bedroom”
“Bedroom”
Previous House
New House
“Living-
Dining”
“Bedroom” “Bedroom”
“Bedroom”
“Bedroom”
“Living-
Dining”
“Bedroom”
“Bedroom”
Matched Labels Matched LabelsCorrespondence of similar rooms
21
23. Room Correspondence 𝜙 𝐶 𝑪
Taking into account area of each room. → Correspondence of similar rooms
Make a correspondence between rooms by using room function labels.
New House
Room Area Comparision ∶
𝑖=1
𝑁
1 −
𝐴𝑖
𝐵𝑐 𝑖
A2 A3 A4A1
B1 B2B3B4
B1
B1
B1
B2 B3 B4
B4 B3B2
B2B3 B4
Smaller
value
Larger
value
Good
Bad
B1
A2 A3
A4
A1
B2 B3
B4
22
24. d
Gaussian function
Layout suggestion taking the previous layout
into account 𝜙 𝑆 𝐹𝑖
1
g
f
The position of furniture
in the previous house
The position of furniture
in the new house
g
f
d(f, g)
d’(f, g)
𝜙 𝑑(𝐹𝑖) = −
𝑓,𝑔∈𝐹 𝑖
exp −
𝑑 𝑓, 𝑔 − 𝑑′
𝑓, 𝑔
2
2𝜎 𝑑
2
Positional relationship
d’(f, g)
d(f, g)
Evaluating the similarity by the positional and orientational relationship
between furniture items.
23
25. 1
θ
Gaussian function
The position of furniture
in the new house
g
f
g
f
The position of furniture
in the previous house
𝜙 𝜃(𝐹𝑖) = −
𝑓,𝑔∈𝐹𝑖
exp −
𝜃 𝑓, 𝑔 − 𝜃′
𝑓, 𝑔
2
2𝜎 𝜃
2
Orientational relationship
𝜃′(𝑓, 𝑔) 𝜃 (𝑓, 𝑔)𝜃 (𝑓, 𝑔)
𝜃′(𝑓, 𝑔)
Evaluating the similarity by the positional and orientation relationship
between furniture items.
Layout suggestion taking the previous layout
into account 𝜙 𝑆 𝐹𝑖
24
52. Conclusion
Automatically computing the furniture layout when one moves
into a new house.
The layout in the new house is computed by assessing
the similarity to the original layout in the previous house.
The visual quality and functionality of the layout are
also taken into account.
A heuristic approach to developing the cost function
for the layout similarity.
There are some limitations in our system.
51
53. Limitations
Moving furniture from one room to another
Can suggest many types of layout
with various furniture combinations.
In terms of room correspondence, need to use different features
such as aspect ratio of a room
Evaluation of a quality of the layouts suggested by the user.
Ask experts from the area of interior design and get feedbacks
from them.
Extend our system to different room types,
e.g. L-shaped rooms.
52
Thank you for introduction.
Hallo.
Paper’s title is Computer Simulation of Furniture Layout when Moving from One house to Another.
This slide shows the contents of my presentation.
First, I’d like to begin with background and motivation of this research as an introduction.
Recently in computer graphics, many researchers have developed computer-aided systems for designing everyday objects.
This enables people to create everyday objects that satisfy his or her particular needs.
So we can apply this technology to many everyday things, such as clothing design, interior and furniture design, architecture design and so on. // In this presentation, we apply this technology to furniture layout design.
// Furniture layout is challenging // because it requires jointly optimizing a variety of functional and visual criteria.
// So, many researchers proposed several methods that help people to arrange the furniture layout.
// These methods automatically suggest a furniture layout for a single room.
// But these methods are not for multiple rooms.
So these systems are not enough for simulating house moving.
// So, we suggest an automatic furniture layout system for multiple rooms.
Next, I’d like to talk about related work.
Many researchers have proposed various methods of furniture layout design.
// This method computes the furniture layout for large spaces.
// This method uses interior design guidelines and suggests a single room furniture layout.
// This method used crowd-sourced datasets for styles of furniture layout.
// However, these methods don’t deal with designing the layout for multiple rooms
In this slide, we show some methods dealing with floor plans and multiple rooms.
// This paper uses a Bayesian network trained on real-world floor plans.
// This method takes into account the functionalities and the design capabilities of buildings.
// This paper automatically generates maps in games using specifically shaped blocks such as rectangular or L or T shaped blocks.
// But there is no method suggesting furniture arrangements.
Next, I’d like to talk about our proposed method.
This slide shows our problem definition.
// When you move into a new house, it is trouble issue to rearrange furniture items.
// Typically, we simulate furniture layout by using printed floor plans.
And there is no method that computes furniture layout for moving.
So // we try to // compute furniture layout for moving into a new house.
// When we try to compute moving, we have two assumptions about how people determine the layout when moving.
// One is to relocate furniture in functionally and geometrically similar rooms in the previous house.
// And the other is that the layout in the new house is similar to that in the previous house.
// So our method is to assign the same or similar function rooms and suggest a similar layout in the new house.
Now we explain our system overview.
// First User inputs // the floor plan of the previous house and its furniture layout.
// and the user also inputs a floor plan of the new house.
// Then computer optimizes and suggests several layouts
// and the user chooses a favorite layout.
// Finally user can see inside of the rooms and check the atmosphere whether they like this layout or not.
In this slide, we explain our approach.
Here are a previous house and a new house.
// Our approach is optimizing a furniture layout in all rooms of the new house.
// We design a cost function here and try to optimize this term.
// This is room correspondence term and
// this is Merrell’s cost function that our method is based on and
// this is the layout similarity term.
// and finally optimize this term and suggest a layout.
Next, we will explain these terms in detail.
// In our method, we design a cost function that takes care of all rooms in the new house.
// For example, there are a previous house and a new house.
// And these labels show the room functions.
// First, we make a correspondence between rooms with similar rooms.
// If there are dining furniture items, we don’t usually move them to this bedroom.
// We usually move them to this living-dining room.
On the other hand
// if there is bedroom furniture items, we don’t move them to this living-dining room
// but move them to these bedrooms.
// So we move furniture items to a room in the new house that is functionally and geometrically similar to the room.
// In other words, we take into account the function and area of each room to measure the quality of the correspondence between rooms in the previous and new house.
// So we define room correspondence term phi_c.
Next,
Using this correspondence, // we assign furniture items and // optimize the layout by using Merrell’s method.
// For each room, we evaluate the functional and visual quality of the layout.
// And we define the functional and visual term phi_m.
Finally, // // we evaluate the similarity of the layout in each room.
// We measure the similarity by the positional and orientational relationships between furniture items.
// So we define a similarity term phi_s
And it consists of // positional term and // orientational term.
Finally we optimize the cost function.
// We employ a Markov chain Monte Carlo sampler to explore the function.
And use the Metropolis-Hastings algorithm.
// Specifically, we define this Boltzmann-like density function and sample the function by using this acceptance probability.
In this slide, we explain room correspondence term in detail.
// we make a correspondence by using room function labels and take into account area of each room.
// there are previous and new house.
// First user labels each room, such as living-dining or bedroom.
// Our system evaluates the room correspondence by these labels.
// In this case, labels between these rooms are matched.
// On the other hand, // // in this case, labels between these rooms are mismatched.
// However, because there are three bedrooms, there are other correspondence.
In this case, labels between these rooms are matched.
// In addition to the label correspondence, we assign similar rooms.
We also take into account area of each room and we assign similar rooms.
// In this correspondence,
// we calculate the area of each room and
// we evaluate the area similarity in this term.
// There are // // many possible combinations.
// and by using this term, the smaller value combination is good correspondence.
Next, we explain layout similarity term in detail.
// we evaluate the similarity by the positional and orientational relationship between furniture items.
//First, let me explain the evaluation of the positional relationship by using this figure.
Left one shows the previous layout and right one shows the new layout.
// we employ a Gaussian function to evaluate the positional relationship.
Let’s consider the furniture items f and g.
// We use the distance d’ between f and g // for the average of the Gaussian function.
// we calculate the distance d and compute the sum of the Gaussian function for all possible pairs of furniture items.
Similarly,
// we calculate orientational relationship.
// use Gaussian function and // Gaussian average is the previous orientation theta’
// and calculate orientation theta and compute the sum of the Gaussian function for all possible pairs of furniture items.
Next, I’d like to talk about our results.
This slide shows our computer used for the following examples.
In our simulation, we used this 14 types of furniture items.
First we show a example, one living-dining and two bedrooms.
// original layout is here.
// and we demonstrated these three types of floor plans and same number of rooms.
First, when we try to rearrange the furniture items in this new house,
Our system suggests this layout.
And you can see that these layouts are similar.
Room correspondence is here.
Here.
Here.
User can check inside of the rooms.
// in every rooms, the layouts are similar to that in the previous house.
And You can enjoy the atmosphere of the new house.
In other examples,
We can also suggest a layout
And in every rooms, these layouts are similar.
And you can see that in every new house room correspondences are appropriate.
Next, we show the other example, one living-dining and three bedrooms.
// original layout is here.
// and we demonstrate these two types of floor plans and same number of rooms.
First, when we try to rearrange the furniture items in this new house,
Our system suggests this layout.
And you can see these layouts are similar.
Room correspondence is here.
Here.
Here.
Here.
User can also check inside of the rooms.
// in every rooms, the layouts are similar to that in the previous house.
And You can also enjoy the atmosphere of the new house.
We tested the suggestions in the same floor plan with different layout.
// you can see // that all layout are the appropriate correspondences // and the similar layouts are suggested.
In other example,
We can also suggest a similar layout.
And you can see // that room correspondences are appropriate.
// Like this // like this // like this
Finally, I’d like to conclude this presentation.
// We proposed a method for automatically computing the furniture layout when one moves into a new house.
The layout in the new house is computed by assessing the similarity to the original layout in the previous house.
At the same time, the visual quality and functionality of the layout are also taken into account.
// This method is a heuristic approach to developing the cost function for the layout similarity.
So there are some limitations in our system.
// we need to // move furniture from one room to another.
// This leads to suggest many types of layout with various furniture combinations.
// In terms of room correspondence, we need to use different features, such as aspect ratio of a room.
// we need to extend our system to different room types, such as L-shaped rooms.
// and we evaluate a quality of the layouts suggested by the user.
And ask experts from the area of interior design and get feedbacks from them.
Finally in addition to address the limitations,
// we would like to collect a large dataset for the layout patterns for the previous and new houses.
// and we find some positional and orientational relationships.
Then by analyzing them,
// we believe we will be able to find a more sophisticated cost function.
