Sebastian Zambanini

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The vision-based detection of hand gestures is one technological enabler for <i>Natural User Interfaces</i> which try to provide a natural and intuitive interaction with computers. In particular, mobile devices might benefit from such a less device-centric but more natural input possibility. In this paper, we introduce our ongoing work on the visual(More)
We present a vision-based approach to ancient coins’ identification. The approach is a two-stage procedure. In the first stage an invariant shape description of the coin edge is computed and matching based on shape is performed. The second stage uses preselection by the first stage in order to refine the matching using local descriptors. Results for(More)
The field of Numismatics provides the names and descriptions of the symbols minted on the ancient coins. Classification of the ancient coins aims at assigning a given coin to its issuer. Various issuers used various symbols for their coins. We propose to use these symbols for a framework that will coarsely classify the ancient coins. Bag of visual words(More)
In a smart home system, a camera-based fall detector at elderly homes leads to immediate alarming and helping. In this paper we propose an approach for the detection of falls based on multiple cameras. Based on semantic driven features, fall detection is done in 3D and fuzzy logic is used to estimate confidence values for different human postures as well as(More)
In the context of ambient assisted living, camera-based fall detectors at elderly homes leads to immediate alarming and helping. In this paper we propose a novel approach for the detection of falls based on multiple cameras. Based on semantic driven features fall detection is done in 2D and each camera decides on its own, if a fall has occurred. Fuzzy logic(More)