Michael Pätzold

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Per pixel adaptive Gaussian mixture models (GMMs) have become a popular choice for the detection of change in the video surveillance domain because of their ability to cope with many challenges characteristic for surveillance systems in real time with low memory requirements. Since their first introduction in the surveillance domain, GMM has been enhanced(More)
In this paper we present a decentralized surveillance network composed of IP video cameras, analysis devices and a central node which collects information and displays it in a 3D model of the complete area. The exchange of information between all components in the surveillance network takes place according to the ONVIF specification, therefore ensuring(More)
INTRODUCTION Type 1 diabetes can be diagnosed at an early presymptomatic stage by the detection of islet autoantibodies. The Fr1da study aims to assess whether early staging of type 1 diabetes (1) is feasible at a population-based level, (2) prevents severe metabolic decompensation observed at the clinical manifestation of type 1 diabetes and (3) reduces(More)
Detecting people carrying objects is a commonly formulated problem which results can be used as a first step in order to monitor interactions between people and objects in computer vision applications. In this paper we propose a novel method for this task. By using gray-value information instead of the contours obtained by a segmentation process we build up(More)
In this paper we present an approach for the efficient computation of optical flow fields in real-time and provide implementation details. Proposing a modification of the popular Lucas-Kanade energy functional based on integral projections allows us to speed up the method notably. We show the potential of this method which can compute dense flow fields of(More)
Advance Driver Assistance Systems (ADAS) have gained huge attention in the last decades. One of the fundamental steps of the video processing chain is the detection of areas where the car can drive through, i.e. free-space. In this paper we present an approach for the detection of free-space which is based on image segmentation and classification of the(More)