Andreas Griesser

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We present a GPU-based foreground-background segmentation that processes image sequences in less than 4ms per frame. Change detection wrt. the background is based on a color similarity test in a small pixel neighbourhood, and is integrated into a Bayesian estimation framework. An iterative MRF-based model is applied, exploiting parallelism on modern(More)
This paper presents a new active range scanning technique suitable for moving or deformable surfaces. It is a 'one-shot' system, in that 3D data are acquired from a single image. The projection pattern consists of equidistant black and white stripes combined with a limited number of colored, transversal stripes which aid in their identification. Instead of(More)
Active 3D acquisition setups currently capture 3D data from a single viewpoint. We propose a system that supports the effective use of multiple structured light modules placed around the object of interest. We show how oppositely positioned modules could work together and how we can avoid those parts of the background that unnecessarily take up computation(More)
This paper presents a novel interactive Projector Calibration for arbitrary Multi-Projector-Camera environments. The method does not require any calibration rig and is not restricted to any special arrangement of the display devices. The cameras in the system need to be precalibrated so that a common world coordinate system can be defined. Each projector is(More)
Cluster-based architectures are very popular in the construction of versatile computer vision and graphics applications. Hereby, computers are connected over a network to perform collaborative processing. Systems which include cameras demand for accurate synchronisation as well as low latencies for short-message data transfers. We present work which(More)
We present a modular system for real-time 3D-scanning of human bodies under motion. The high-resolution shape and colour appearance is captured by several scanning units positioned around the object of interest. Each of these units performs a foreground-background segmentation and computes a valid depth-range for the spatially neighbouring units. Multiple(More)
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