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13 results

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Michael Black

Director

My research focuses on computing and understanding motion in the world from video. In generic scenes I study optical flow (the 2D image motion) and how it relates to physical properties of the world including 3D shape, material, illumination, and motion. I also develop new methods to capture natural, complex, human and animal motion for applications in computer vision, animation, and neuroscience.

Office: N3.019
+49 7071 601 1801


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Andreas Geiger

Professor, University of Tübingen
Max Planck Research Group Leader

I am interested in computer vision and machine learning with a focus on 3D scene understanding, parsing and reconstruction. During my Ph.D. I have developed probabilistic models for 3D traffic scene understanding from movable platforms.

Office: S2.016
+49 7071 601 1830


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Siyu Tang

Research Group Leader

I am interested in the intersection between computer vision and machine learning with a focus on holistic visual scene understanding. In particular, I am interested in analyzing and modeling people in our complex visual scenes.

Office: N3.009


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Melanie Feldhofer

Department Manager

Office: N3.018
+49 7071 601 1800


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Nicole Overbaugh

Administrative Assistant

Office: N3.018
+49 7071 601 1800


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Aamir Ahmad

Research Scientist

I am leading the project AirCAp: Micro Aerial Vehicles (MAV)-based Outdoor motion CAPture. In this project, we have developed MPC-based formation-control methods to jointly perceive moving targets through multiple MAVs, each equipped with a monocular camera. Real robot experimental results have not only validated our approach but have set a strong foundation for future research direction in this context. For further information, please visit the project page.

Office: N3.007
+49 7071 601 1816


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Tsvetelina Alexiadis

Trial Coordinator

I work with computer vision researchers to coordinate, schedule and run human subjects trials involving body shape and motion analysis at the Perceiving Systems Department. To collect data we use several computer vision technologies, including our unique 3D and 4D body scanners and our new 4D face scanner.

Office: N3.016
+49 7071 601 1805


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Timo Bolkart

Postdoctoral Researcher

My research focus and interest is in the area of 3D computer vision and computer graphics. I am especially interested in non-rigid shape analysis, statistical modelling of various kinds of shapes, and the analysis of motion data. A complete list of publications can be found here: https://sites.google.com/site/bolkartt/publications

Office: N3.009


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Nima Ghorbani

Research Engineer


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Andrea Keller

Project Coordinator

I coordinate our department's research trials. We collect data on human body shape and pose. This includes 3D and 4D body scans, face scans, anthropometric measurements, Motion Capture, and further (experimental) technologies. I recruit participants, schedule, manage appointments, create protocols of poses and movements and gain data according to our scientists' needs. Also, I process the data and take care of data security. Besides that, I am responsible for organising lab tours for visitors of our department.

Office: N3.016
+49 7071 601 1803


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Benjamin Pellkofer

IT Sys Admin


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Sergi Pujades

Postdoctoral Researcher

My research aims at understanding the world through the capture and analysis of heterogeneous data (MRI, CT, Point clouds, images, ...) in order to create applied digital instruments, that allow, for example, to generate novel views from a scene, to infer the human shape from a clothed scan, or to predict the amount of adipose tissue of a person from surface observations. To address this challenge, I adopt the approaches of Computer Vision, Signal Processing, Computer Graphics and Statistical Models. My research is often multi-disciplinary, as I need to combine knowledge from these different domains.

Office: N3.009


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Dimitris Tzionas

Postdoctoral Researcher

For my PhD I worked with Juergen Gall on Hand-Object Interaction. In particular we focused on capturing the motion of hands interacting with each other and/or with a rigid or an articulated object. We further studied the case of acquiring missing knowledge about the manipulated object, i.e. its shape or its kinematic model.

Office: N3.009