Research

Unstructured VBR

We present an algorithm designed for navigating around a performance that was filmed as a "casual" multi-view video collection: real-world footage captured on hand held cameras by a few audience members. The objective is to easily navigate in 3D, generating a video-based rendering (VBR) of a performance filmed with widely separated cameras. Casually filmed events are especially challenging because they yield footage with complicated backgrounds and camera motion. Such challenging conditions preclude the use of most algorithms that depend on correlation-based stereo or 3D shape-from-silhouettes.

Marker-less Motion Capture of Interacting People

The project aims to infer the poses of a character acting in a environment filmed by a set of video cameras. Once his poses are estimated, a free-viewpoint video of the entire action can be genertated.

Urban Location Recognition on Mobile Device

We address the problem of large scale place-of-interest recognition in cell phone images of urban scenarios. Here, we go beyond what has been shown in earlier approaches by exploiting the nowadays often available 3D building information (e.g. from extruded floor plans) and massive street-view like image data for database creation.

Vision Controlled MAV

This is a multi-year, student-driven project to create autonomous flying systems using pure onboard processing. We are focused on computer vision on Micro Air Vehicles, which allowed us to win the EMAV 2009 Indoor Autonomy Competition.

sFly: Swarm of Micro Flying Robots!

The obective of the sFly project is to develop several small and safe helicopters which can fly autonomously in city-like enviroments and which can be used to assist humans in tasks like rescue and monitoring.