The student will work with me on a topic in the general area of marker-less dynamic scene reconstruction, an area where the group also receives funding through an ERC Starting Grant. The goal is to rethink the basic algorithmic concepts of marker-less motion capture, dynamic (4D) scene reconstruction, performance capture and 3D Video.
We develop new 4D reconstruction methods that, unlike current approaches, capture detailed models of dynamic shape and appearance
(e.g. of humans, human hands, human faces or general dynamic scenes)
in complex real world environments outside of the a lab using only a low number of, or just a single camera.
Such techniques are on high demand, and for instance
essential building blocks for next generation human-computer and human-robot interfaces, or believable AR and VR experiences.
We also work on new algorithms for image-based estimation of lighting and reflectance in general uncontrolled scenes,
and we utilize these estimates for improved 4D reconstruction, high quality shape estimation, and relighting.
Recently, we put a strong focus on developing approaches
that capture high quality models in real-time from sparse sensor setups, even just a single camera view. Here, we
also investigate new machine learning techniques for improved dense model reconstruction.
Some of our research results also form the basis for our
award-winning local startup company www.thecaptury.com.
Applicants should have a Bachelor, preferably Master degree, in computer science or a closely related field.
Course work and research experience in one or more of the following areas is desirable: multi-view / 3D scene reconstruction methods, 4D reconstruction, marker-less performance capture, marker-less motion capture, tracking algorithms, 3D Video, general computer graphics concepts. Course work / research experience in machine learning is an additional plus.
Applicants should have an excellent academic record; publications in one of the above areas are a plus. A candidate should be fluent in written and spoken English and be willing to travel. Full funding and benefits are provided.
If you are interested in this PhD position, please send a complete application package, including a CV, a research statement, transcripts and certificates, and the contacts of two references by
>>>>>>> Jan 6 2016 <<<<<<<<<<
Prof. Dr. Christian Theobalt
MPI for Informatics
please add the tag [PhD Application] in the subject of your Email.
About Christian Theobalt and the GVV group
Christian Theobalt is a Professor of Computer Science and the head of the research group "Graphics, Vision, & Video" at the Max-Planck-Institute for Informatics, Saarbruecken, Germany. From 2007 until 2009 he was a Visiting Assistant Professor in the Department of Computer Science at Stanford University.
Most of his research deals with algorithmic problems that lie on the boundary between the fields of Computer Vision and Computer Graphics, such as static and dynamic 3D scene reconstruction and marker-less motion capture, computer animation, appearance and reflectance modeling, machine learning for graphics and vision, new sensors for 3D acquisition, advanced video processing, as well as image- and physically-based rendering.
For his work, he received several awards, including the Otto Hahn Medal of the Max-Planck Society in 2007, the EUROGRAPHICS Young Researcher Award in 2009, and the German Pattern Recognition Award 2012. In 2015 he was elected one of the top 40 innovation leaders under the age of 40 in Germany by the magazine Capital. Further, in 2013 he was awarded an ERC Starting Grant by the European Union, the most prestigious and most competitive grant for individual researchers. He is a Principal Investigator and a member of the Steering Committee of the Intel Visual Computing Institute in Saarbruecken. He is also a co-founder of a spin-off company from his group - www.thecaptury.com - that is commercializing marker-less motion and performance capture solutions.
The group Graphics, Vision & Video maintains a close collaboration with international academic partners and lives a very collaborative team-oriented working style within the group itself. Check out our team (link)
About the Environment
The Max-Planck Institute for Informatics (MPI-INF) (www.mpi-inf.mpg.de)
is one of the world's leading research institutes in Computer Science in general, and Visual Computing in particular.
It is located on the campus of Saarland University in Saarbruecken, Germany. MPI-INF is embedded in a unique cluster of
computer science research. Around 400 PhD students in CS do research in the different institutes
on campus under the roof of a joint CS graduate school.
In immediate neighborhood on campus, there are several other computer science research institutes of world renown
with which close collaborations exist: the German Research Center for
Artificial Intelligence (DFKI), the Max-Planck-Institute for Software
Systems, the Institute for Bioinformatics, the Excellence Cluster
Multimodal Computing and Interaction, the new federal research center on IT Security, Privacy and Accountability (CISPA),
and the Computer Science Department of Saarland University. The Leibniz Center for Informatics
in Schloss Dagstuhl is also located
nearby. The Intel Visual Computing Institute (IVCI) on campus further strenghtens the
visual computing research focus in Saarbruecken.