Sybil detection is a crucial task to protect online social networks (OSNs) against intruders who try to manipulate automatic services provided by OSNs to their customers. In this paper, we first discuss the robustness of graph-based Sybil detectors SybilRank and Integro and refine theoretically their security guarantees towards more realistic assumptions. After that, we formally introduce adver...

A new approach has been developed for accurate and fast recognition of traffic signs based on human vision models. It applies colour appearance model CIECAM97 to segment traffic signs from the rest of scenes. This model takes viewing conditions into account and can recognise colours as accurate as an average observer invariant of lighting sources, background, and surrounding colours. A Behaviou...

A framework for general gesture recognition is presented and tested with isolated signs of sign language. Other than common systems for sign language recognition, this framework makes use of Kinect, a depth camera developed by Microsoft and PrimeSense, which features easy extraction of important body parts. Recognition is done using hidden Markov models with a continuous observation density. Th...

An open source framework for general gesture recognition is presented and tested with isolated signs of sign language. Other than common systems for sign language recognition, this framework makes use of Kinect, a depth camera which makes real-time 3D-reconstruction easily applicable. Recognition is done using hidden Markov models with a continuous observation density. The framework also o ers ...

This paper originates from a cooperation of Daimler-Benz AG, the University of Paderborn, and our group, within the European PROMETHEUS project. Common aim is the development of a traf-c sign recognition (TSR) system. The Paderborn group provides gray-level image evaluation, Daimler-Benz AG pictogram identiication, and our group color image evaluation. Our approach to TSR is based on a fast and...

This PhD thesis investigates the image sequence labeling problems optical character recognition (OCR), object tracking, and automatic sign language recognition (ASLR). To address these problems we investigate which concepts and ideas can be adopted from speech recognition to these problems. For each of these tasks we propose an approach that is centered around the approaches known from speech r...

Current approaches to sign recognition by computer generally have at least some of the following limitations: they rely on laboratory conditions for sign production, are limited to a small vocabulary, rely on 2D modeling (and therefore cannot deal with occlusions and off-plane rotations), and/or achieve limited success. Here we propose a new framework that (1) provides a new tracking method les...

This article proposes a general extension of the error correcting output codes framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. In particular, this extension supports the use of both online example incremental and batch classifiers as base learners. The extension of the traditional problem...

The grooming factor C of a WDM optical network is the number of connections that can share the bandwidth of each wavelength and the process of grouping the requests that will share each wavelength is called traffic grooming. The goal of traffic grooming is either to reduce the transmission cost by reducing the number of wavelengths or to reduce the hardware cost by reducing the number of Add-Dr...

There exists significant variation between sign language recognition processes across the world, although there are many similarities. Pre-processing, feature extraction and classification are the three major steps involved in the sign language recognition process. An analysis of scientific literature indicates the potential of various methods in achieving significantly high accuracy in image r...