Hans-Joachim Böhme

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—The paper describes progress achieved in our long-term research project SHOPBOT, which aims at the development of an intelligent and interactive mobile shopping assistant for everyday use in shopping centers or home improvement stores. It is focusing on recent progress concerning two important methodological aspects: (i) the on-line building of maps of the(More)
— Simultaneous Localization And Mapping (SLAM) has been an important field of research in the robotics community in recent years. A successful class of SLAM algorithms are Rao-Blackwellized Particle Filters (RBPF), where the particles approximate the pose belief distribution, while each particle contains a separate map. So far, RBPF with landmark based(More)
This paper describes a user detection system which employs a saliency system working on an omnidirectional camera delivering a rough and fast estimate of the position of a potential user. It consists of a vision (skin color) and a sonar based component , which are combined to make the estimate more reliable. To make the skin color detection robust under(More)
We present a novel omnivision-based robot localiza-tion approach which utilizes the Monte Carlo Lo-calization (MCL) [2], a Bayesian filtering technique based on a density representation by means of particles. The capability of this method to approximate arbitrary likelihood densities is a crucial property for dealing with highly ambiguous localization(More)
— In this paper, the people tracking system of a mobile shopping assistant based on a SCITOS-G5 platform is explained in detail. The robot has two tasks, to find people requiring assistance and to guide a user to a target without losing contact. For that purpose, a probabilistic model and a Bayesian update scheme have been developed, where data of various(More)
In this paper we compare two models for extracting features from face images and several neural classifiers for their applicability to classify gender, age, facial expression, and identity. These models are i) a description of face images by their projection on independent base images and ii) an Active Appearance Model which describes the shape and grey(More)
Recently there is an increasing interest in video based interface techniques, allowing more natural interaction between users and systems than common interface devices do. Here, we present a neural architecture for user localisa-tion, embedded within a complex system for visually-based human-machine-interaction (HMI). User's localisation is an absolute(More)
The paper describes a multi-modal scheme for human-robot interaction suited for a wide range of intelligent service robot applications. Operating in un-engineered, cluttered, and crowded environments, such robots have to be able to actively contact potential users in their surroundings and to offer their services in an appropriate manner. Starting from a(More)
We present a neural architecture for gesture-based interaction between a mobile robot and human users. One crucial problem for natural interface techniques is the robustness under highly varying environmental conditions. Therefore, we propose a multiple cue approach for the localisation of a potential user in the operation eld, followed by the aquisition(More)