Christian X. Ries

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We provide an overview of state-of-the-art approaches to visual adult image recognition which is a special case of one-class image classification. We present a representative selection of methods which we coarsely divide into three main groups. First we discuss color-based approaches which rely on the intuitive assumption that adult images usually feature(More)
This paper presents a method for creating a discriminative color model for a given object class based on color occurrence statistics. A discriminative color model can be used to classify individual pixels of images with regards to whether they may belong to the wanted object. However, in contrast to existing approaches, we do not exploit pixel-wise object(More)
Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ABSTRACT In this paper we present a(More)
We present an approach for automatically devising object annotations in images. Thus, given a set of images which are known to contain a common object, our goal is to find a bounding box for each image which tightly encloses the object. In contrast to regular object detection, we do not assume any previous manual annotations except for binary global image(More)
In this paper we propose a framework to address the reassem-bly of shredded documents. Inspired by the way humans approach this problem we introduce a novel algorithm that iteratively determines groups of fragments that fit together well. We identify such groups by evaluating a set of constraints that takes into account shape-and content-based information(More)