ECO3D is an initiative started and lead by Jeppe R. Frisvad, Knut Conradsen, and Henrik Aanæs, to coordinate our research activities in sensors and 3D geometric and radiometric modeling in relation to the cyber-physical 3D ecosystem. This ecosystem is an abstraction of the fact that we oftentimes wish to manipulate the physical world based on sensor generated digital or cyber models of this physical world. This is illustrated in the following diagram.

This ecosystem also encompasses much of the research we do at the Section for Image Analysis and Computer Graphics at the Technical University of Denmark, and is as such a nice framework for exploiting the possible synergies within our group. Examples of this ecosystem are

Furthermore, we have noticed that most of the individual parts of this ecosystem are vibrant research topics, but that very few consider these parts as a whole. We believe that there is significant potential in such a holistic approach, and have the good fortune to take it, in that we have experts within most - if not all - of the individual parts on 'sensors' and 'synthesis prediction & modeling' and have close collaboration with top researchers doing actuators, like 3D print and robotics.

As seen under People, this initiative has a sufficient number of participants, working on parts of the ecosystem. A benefit of taking the holistic ecosystem approach to our research is that it also enforces relevant performance metrics on our research in the individual parts. In 2015, the first year of the initiative, our collaboration has focus on

We also have had a lot of activities in the individual parts via the existing projects of the individual participants.

Current research projects

Multi-View BRDF

Having densly sampled BRDFs of the surface of each object in a given scene allows for photorealistic rendering of that scene. This project aims at creating a database of 3D scenes composed of simple geometries, includes surface BRDFs.

Non-Rigid Structure From Motion

We create a realistic dataset for evaluation of Non-Rigid Structured From Motion algorithms. The dataset provides a dense point set with an accurate ground truth. This is accomplished through stop-motion animated animatronics with dense structured light scanning for each frame.

Transparency

We have created a multi-view stereo (MVS) dataset where the focus is on reconstruction of geometry and appearance. Three glass objects with different radiometric properties are selected and multiple MVS scenes are captured, reconstructed and rendered.

Appearance

We create efficient rendering techniques and mathematical models that predict the appearance of materials from their physical microstructure. The goal is to interactively compute realistic images of real-world materials.

Recent Publications

Designing for Color in Additive Manufacturing [2016]

E. R. Eiriksson, A. Luongo, J. R. Frisvad, D. B. Pedersen, H. Aanæs
Proceedings of ASPE 2016 Summer Topical Meeting on Dimensional Accuracy and Surface Finish in Additive Manufacturing

Interactive Appearance Prediction for Cloudy Beverages [2016]

A. D. Corso, J. R. Frisvad, T. K. Kjeldsen, J. A. Bærentzen
Workshop on Material Appearance Modeling (MAM 2016) , The Eurographics Association

Hybrid fur rendering: combining volumetric fur with explicit hair strands [2016]

T. G. Andersen, V. Falster, J. R. Frisvad, N. J. Christensen
The Visual Computer , 32, 739—749

Large-Scale Data for Multiple-View Stereopsis [2016]

H. Aanæs, R. R. Jensen, G. Vogiatzis, E. Tola, A. B. Dahl
International Journal of Computer Vision , Springer, 1—16

Interactive directional subsurface scattering and transport of emergent light [2016]

A. D. Corso, J. R. Frisvad, J. Mosegaard, J. A. Bærentzen
The Visual Computer

On Optimal, Minimal BRDF Sampling for Reflectance Acquisition [2015]

J. B. Nielsen, H. W. Jensen, R. Ramamoorthi
ACM Transactions on Graphics (TOG) , 34, xxx-xxx

Our 3D Vision Data-Sets in the Making [2015]

H. Aanæs, K. Conradsen, A. D. Corso, A. B. Dahl, A. D. Bue, M. Doest, J. R. Frisvad, S. H. N. Jensen, J. B. Nielsen, J. D. Stets, G. Vogiatzis
Conference on Computer Vision and Pattern Recognition 2015 , Institute of Electrical and Electronics Engineers

Quality Assurance Based on Descriptive and Parsimonious Appearance Models [2015]

J. B. Nielsen, E. R. Eiriksson, R. L. Kristensen, J. Wilm, J. R. Frisvad, K. Conradsen, H. Aanæs
Workshop on Material Appearance Modeling , The Eurographics Association

Directional Dipole Model for Subsurface Scattering [2014]

J. R. Frisvad, T. Hachisuka, T. K. Kjeldsen
ACM Transactions on Graphics , 34, 5:1—5:12

Large scale multi-view stereopsis evaluation [2014]

R. R. Jensen, A. Dahl, G. Vogiatzis, E. Tola, H. Aanæs
2014 IEEE Conference on Computer Vision and Pattern Recognition , 406—413

Real-Time Rendering of Teeth with No Preprocessing [2012]

C. T. Larsen, J. R. Frisvad, P. D. E. Jensen, J. A. Bærentzen
Advances in Visual Computing (Proceedings of ISVC 2012) , Springer, 7432, 334—345

Predicting the Appearance of Materials Using Lorenz-Mie Theory [2012]

J. R. Frisvad, N. J. Christensen, H. W. Jensen
The Mie Theory: Basics and Applications , 169, 101—133

Digital prototyping of milk products [2012]

J. R. Frisvad, O. H. A. Nielsen, J. L. Skytte, M. K. Misztal, A. L. Dahl
Food Colloids 2012 Posters , P53

Light, Matter, and Geoemtry: The Cornerstones of Appearance Modelling [2008]

J. R. Frisvad
Department of Informatics and Mathematical Modelling, Technical University of Denmark

Computing the Scattering Properties of Participating Media Using Lorenz-Mie Theory [2007]

J. R. Frisvad, N. J. Christensen, H. W. Jensen
ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH 2007) , 26, 60:1—60:10