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Welcome to my page at the Chair for Image Understanding and Knowledge-Based Systems. I am a graduate student working on my Ph.D. thesis under the supervision of Prof. Radig.

Current work: Since 07/2009, I am responsible for the integration of the Multi-Joint Vision (MuJoVision) project, which is part of the cluster of excellence for Cognition in Technical Systems (CoTeSys). The project aims at obtaining image data in real-time from a large set of cameras simultaneously for further processing in Computer Vision applications, e.g. person tracking and gesture recognition.

Further research: Other research interests are located within the field of Human-Computer Interaction (HCI). Particular interest is the interpretation of human visual communication channels such as Facial Expression Recognition and Gesture Recognition.

Bio: I recieved a Diploma (Dipl. Inf. univ.) degree from the TU München in 06/2009. My diploma thesis topic was "Cross-Database Facial Expression Classification Using Three-Dimensional Geometrically Deformable Models".

Where to find me: My office is at the CoTeSys Central Robotics Laboratory (CCRL) which is located in Barer Str. 21, 4th Floor in downtown munich, near the TU München central complex.

Research Topics

  • Model-Based Image Interpretation
  • Face Detection, Face Model Fitting, Head Tracking
  • Facial Expression Recognition, Emotion Recognition
  • Human Motion Capture, Tracking and Analysis

Current Research Projects

  • MuJoVision : The Multi-Joint Vision project aims at providing image data obtained simultaneously from a large number of cameras in real time for further processing in Computer Vision applications. It involves the integration of a flexibly expandable architecture and interface for distributed Computer Vision applications. The project is part of a Multi-Joint Action scenario developed for the CoTeSys cluster of excellence, and the data obtained is used to generate tracking information for Human-Computer Interaction and monitoring tasks.

Former Research Projects

  • Face Image Analysis : Recent progress in the field of Computer Vision allows intuitive interaction via gesture or facial expressions between humans and technical systems. This project aims at determining facial expressions from camera images in real-time. Model-based image interpretation techniques have proven to be a successful method for extracting such high-level information from single images and image sequences. Models rely on a priori knowledge to reduce the large amount of image data to a small number of model parameters. This representation of the image content facilitates and accelerates the subsequent interpretation task. In order to extract high-level information, model parameters have to be estimated that best describe the face within a given image. However, correctly estimated model parameters forms the basis of various more applications such as gaze detection or gender estimation. Our demonstrator for facial expression estimation has been presented at several events with political audience and on TV.

Teaching General

 

Selected Publications

For the full list of my Publications please see the Publications section.

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