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Establishing a properly illuminated environment is essential to human well-being as it affects behaviour, comfort, health, efficiency, safety and security. Cities are alive 24 hours a day and yet, planners usually focus on the daylight hours. Improving the energy profile of structures and cities is a long-standing goal, along with minimizing lighting pollution. Planning cities or designing structures under such constraints and goals stresses the involvement of lighting experts and the creation of intelligent and precise tools to assist in the process.

Practical lighting design relies on empirical formulas and statistical averages, which are more often than not unable to capture the actual geometric qualities of the intended spaces and the true light transport within. Illumination simulation is nowadays utilized for a more accurate prediction of the resulting lighting under different conditions. However, the placement and configuration of luminaires and lighting structures is a predominately manual, trial and error process.

Lighting design can greatly benefit from automatic tools that aid the designer in selecting the lighting parameters and modifying the environment in order to achieve the desired effects. Goal-driven algorithms can enable the specification of desired illumination goals and various constraints and an optimization framework will optimize the different parameters of the environment in order to achieve them.

LOTUS project aims to investigate and develop goal-driven computational lighting design methods for large-scale constructions and environments, which can be directly applicable to architectural and civil engineering design cycles in order to improve energy efficiency, lighting quality and ease the design lifecycle itself.

Our research will be focused on large scale luminaire placement, and optimization and automatic opening design that respects functional and aesthetic constraints and exploits both natural and artificial lighting. This project will conduct research in the following directions:

Opening Design

Investigate approaches that solve the opening design problem for various types and sizes of openings under constrained environments.
Experiment with techniques that combine artificial and natural illumination in order to achieve desired results and model the problem in a non-discretized manner.
Seek solutions that will apply, not only to simple walls or rooms, but on entire buildings, respecting complex functional and aesthetic constraints (symmetries, uniform distances across floors, etc.) in the process.

Urban Lighting Design

Investigate solutions that can be applied on the large scale of urban environments under many optimization variables and constraints.
Formulate the problem as an optimization function and investigate approaches that place and parameterize lighting fixtures, automatically and optimally selected from a diverse set of available lighting fixtures.
Experiment with formulating the problem in a hierarchical manner, to better handle the expansive scale of luminaire deployment.
Examine the potential simultaneous optimization of occluding auxiliary geometry and reflectors to minimize lighting pollution even more.

Project Timeline

Aug, 2022
Project Start
Nov, 2022
STAR on Opening and Urban Lighting Design
Feb, 2023
Eurographics 2023 Publication
Aug, 2023
Computer Graphics International 2023 Publications
Apr, 2024
Eurographics 2024 Publication
Apr, 2024
Project End

News

Eurographics 2024 Publication

Eurographics 2024 Publication

March 27, 2024

Our paper has been accepted for publication on Eurographics 2024!!

CGI 2023 Publications

CGI 2023 Publications

August 8, 2023

Our two papers have been accepted for publication on Computer Graphics International 2023!!

Eurographics 2023 Publication

Eurographics 2023 Publication

February 17, 2023

Our paper has been accepted for publication on Eurographics 2023!!

STAR

STAR

November 30, 2022

State of the art report is here!! Get it in here.

LOTUS is Alive!

LOTUS is Alive!

August 26, 2022

Light Optimization for Urban Spaces Project has officially started!!

Publications

A Generative Approach to Light Placement for Street Lighting

A Generative Approach to Light Placement for Street Lighting

I. Evangelou, N. Vitsas, G. Papaioannou, A. Gkaravelis
Eurographics 2024 - short paper track

Abstract. The design of plausible and effective street lighting configurations for arbitrary urban sites should attain predetermined illuminance levels and adhere to specific layout intentions and functional requirements. This task can be time consuming, even for automated solutions, since there exists an one-to-many mapping between lighting options and illumination goals. In this work, we propose a generative approach for this task, based on an adversarial optimisation scheme. Our proposed method effectively overcomes these task-specific limitations by providing a range of viable solutions that adhere to the input constraints and can be generated within an interactive design life cycle.

Content: Paper, Presentation, Video, Source Code

Opening Design using Bayesian Optimization

Opening Design using Bayesian Optimization

N. Vitsas, I. Evangelou, G. Papaioannou, A. Gkaravelis
Virtual Reality and Intelligent Hardware 2023, proc. CGI 2023

Abstract. Opening design is a major consideration in architectural buildings during early structural layout specification. Decisions regarding the geometric characteristics of windows, skylights, hatches, etc., greatly impact the overall energy efficiency, airflow and appearance of a building, both internally and externally. In this work, we employ a goal-based, illumination-driven approach to opening design using a Bayesian Optimization approach, based on Gaussian Processes. A method is proposed that allows a designer to easily set lighting intentions along with qualitative and quantitative characteristics of desired openings. All parameters are optimized within a cost minimization framework to calculate geometrically feasible, architecturally admissible and aesthetically pleasing openings of any desired shape, while respecting the designer's lighting constraints.

Content: Paper, Presentation, Source Code

A Neural Builder for Spatial Subdivision Hierarchies

A Neural Builder for Spatial Subdivision Hierarchies

I. Evangelou, G. Papaioannou, K. Vardis, A. Gkaravelis
Visual Computer 2023, proc. CGI 2023

Abstract. Spatial data structures, such as k-d trees and bounding volume hierarchies, are extensively used in computer graphics for the acceleration of spatial queries in ray tracing, nearest neighbour searches and other tasks. Typically, the splitting strategy employed during the construction of such structures is based on the greedy evaluation of a predefined objective function, resulting in a less than optimal subdivision scheme. In this work, for the first time, we propose the use of unsupervised deep learning to infer the structure of a fixed-depth k-d tree from a constant, subsampled set of the input primitives, based on the recursive evaluation of the cost function at hand. This results in high-quality upper spatial hierarchy, inferred in constant time and without paying the intractable price of a fully recursive tree optimisation. The resulting fixed-depth tree can then be further expanded, in parallel, into either a full k-d tree or transformed into a bounding volume hierarchy, with any known conventional tree builder. The approach is generic enough to accommodate different cost functions, such as the popular surface area and volume heuristics. We experimentally validate that the resulting hierarchies have competitive traversal performance with respect to established tree builders, while maintaining minimal overhead in construction times.

Content: Paper, Presentation, Source Code

Parallel Transformation of Bounding Volume Hierarchies into Oriented Bounding Box Trees

Parallel Transformation of Bounding Volume Hierarchies into Oriented Bounding Box Trees

N. Vitsas, I. Evangelou, G. Papaioannou, A. Gkaravelis
Computer Graphics Forum 2023, proc. Eurographics 2023

Abstract. Oriented bounding box (OBB) hierarchies can be used instead of hierarchies based on axis-aligned bounding boxes (AABB), providing tighter fitting to the underlying geometric structures and resulting in improved interference tests, such as ray-geometry intersections. In this paper, we present a method for the fast, parallel transformation of an existing bounding volume hierarchy (BVH), based on AABBs, into a hierarchy based on oriented bounding boxes. To this end, we parallelise a high-quality OBB extraction algorithm from the literature to operate as a standalone OBB estimator and further extend it to efficiently build an OBB hierarchy in a bottom up manner. This agglomerative approach allows for fast parallel execution and the formation of arbitrary, high-quality OBBs in bounding volume hierarchies. The method is fully implemented on the GPU and extensively evaluated with ray intersections.

Content: Paper, Presentation, Source Code

Content

State of the Art Report on Opening and Urban Lighting Design

State of the Art Report on Opening and Urban Lighting Design

(Public project deliverable D8)
Nikolaos Vitsas, Iordanis Evangelou, Georgios Papaioannou, Eleni Kovanidou, Anastasios Gkaravelis

Description. This report presents a thorough investigation of the complex and active research area in both opening and urban lighting design.

Parallel Transformation of Bounding Volume Hierarchies into Oriented Bounding Box Trees

Parallel Transformation of Bounding Volume Hierarchies into Oriented Bounding Box Trees

(teaser video of our publication)
N. Vitsas, I. Evangelou, G. Papaioannou, A. Gkaravelis

Description. Teaser video for our publication on Eurographics 2023. Credits: G. Papaioannou and N. Vitsas

Poster of our recent research progress

Poster of our recent research progress

Description. A poster that showcases our recent research progress.

A Generative Approach to Light Placement for Street Lighting

A Generative Approach to Light Placement for Street Lighting

(Eurographics fast forward video)
I. Evangelou, N. Vitsas, G. Papaioannou, A. Gkaravelis

Description. Teaser video for our publication on Eurographics 2024.

Research Team

The LOTUS team shares a common goal of making virtual worlds prettier. We hope that LOTUS will help the community develop, share and distribute knowledge on ray tracing in order to make it far more accessible to everyone. As of this writing. LOTUS's home is the AUEB computer graphics group. Our team is passionate about both cutting edge computer graphics research as well as the spread of computer graphics knowledge. We welcome any kind of feedback regarding future directions, feature enhancement and plain bug fixes.

Principal Investigator / Postdoctoral Researcher

Anastasios Gkaravelis

Principal Investigator / Postdoctoral Researcher

born in Larissa, Greece in 1989. He received his Ph.D. degree in 2019 in the field of Computer Graphics from the Department of Informatics at the Athens University of Economics and Business, under the supervision of Prof. Georgios Papaioannou. The subject of his doctoral thesis was "Efficient Algorithms for Inverse Lighting Design". He has also received B.Sc. and M.Sc. degrees in Computer Science from the same department in 2013 and 2016, respectively. His research interests are focused on computer graphics and, in particular, real-time and offline global illumination algorithms and photorealistic rendering.

Researcher / PhD Candidate

Nick Vitsas

Researcher / PhD Candidate

was born in Athens, Greece in 1989. He received his B.Sc. and M.Sc. in Computer Science from the Department of Informatics at the Athens University of Economics and Business. Both his B.Sc. and M.Sc. thesis were on real-time global illumination techniques. During his M.Sc. studies he also worked as a research software engineer at the Athena Research and Innovation Centre in Athens, working on the European co-financed project GeoKnow. His research interests are focused on real-time and offline photorealistic rendering and high-performance parallel computing. He is currently pursuing his Ph.D. on photorealistic simulation and optimization of lighting conditions at the Department of Informatics of the Athens University of Economics and Business under the supervision of Prof. Georgios Papaioannou.

Researcher / PhD Candidate

Iordanis Evangelou

Researcher / PhD Candidate

was born in Athens, Greece in 1990. He received a 4-year B.Sc. in Computer Science from the Department of Informatics at the Athens University of Economics and Business and an M.Sc. in Computer Science from the same department. He is currently a doctoral student under the supervision of Georgios Papaioannou and his main field of research is high-performance photo-realistic rendering and machine learning methods for computer graphics.

Domain Expert / Photographer

Eleni Kovanidou

Domain Expert / Photographer

is a dedicated and skillful photographer with 20 years of work experience in both studio and outdoors photography. Competent in capturing high quality images and organizing materials for photoshoots, she has worked in numerous lighting-sensitive and demanding in terms of illumination accuracy projects, as well as architecture and artwork photography.

Advisor / Associate Professor

Georgios Papaioannou

Advisor / Associate Professor

born in Athens, Greece in 1974, is an Associate Professor at the Department of Informatics of the Athens University of Economics and Business (AUEB) and head of the AUEB computer graphics group. His research is focused on real-time computer graphics algorithms, photorealistic rendering, shape analysis and geometry processing. He received a 4-year BSc in Computer Science in 1996 and a PhD degree in Computer Graphics and Shape Analysis in 2001, both from the National and Kapodestrian University of Athens, Greece. Since 1997, he has worked as a research fellow in many research and development projects. From 2002 till 2007 he worked as a software engineer in virtual reality systems at the Foundation of the Hellenic World. Prof. Papaioannou has been teaching elementary and advanced computer graphics, programming and human-computer interaction courses since 2002 and he has been the principal investigator for AUEB in many EU and nationally funded projects as well as R&D collaborations with the industrial sector. Prof. Papaioannou has more than 75 publications in peer-reviewed international scientific journals, conference proceedings and volumes, with more than 1300 citations to his work. He is also a member of ACM, SIGGRAPH, Eurographics Association and has been a member of the program committees of many conferences in the above fields.