Keywords: Computer Vision, 3D Interaction
Abstract
Time-of-Flight cameras provide a novel means of acquiring depth information in a scene in real-time. In this project, we focus on analyzing human motion using this imaging device. We develop methods for capturing the full-body pose in 3D form
ToF? camera data and for recognizing activities performed by a person. In particular, we investigate learning-based approaches that allow us to predict full-body poses and classify performed activities based on prior knowledge learned in a training phase. We also explore methods for direct, discriminative pose estimation without relying on a training phase.
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Visit our lab at Garching.
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Loren Schwarz for available student projects within this research project.