- Full text PDF available (9)
- This year (0)
- Last 5 years (9)
- Last 10 years (14)
Journals and Conferences
This article introduces Hybreed, a software framework for building complex context-aware applications, together with a set of components that are specifically targeted at developing hybrid, context-aware recommender systems. Hybreed is based on a concept for processing context that we call dynamic contextualization. The underlying notion of context is very… (More)
Detecting and tracking people and groups of people is a key skill for intelligent vehicles, interactive systems and robots that are deployed in humans environments. In this paper, we address the problem of detecting groups of people from learned social relations between individuals with the goal to reliably track group formation processes. Opposed to… (More)
We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the… (More)
In this paper, we propose a generic framework to generate context-aware recommendations for both single users as well as groups. We present the the concept of context views and a corresponding architecture implementing the framework as well as exemplary recommendation workflows for group recommendations.
In this paper, we introduce a framework for modular generation of context-aware recommendations. The components of this framework include context sensors, recommender algorithms and utility modules (converters and filters), all realized as so-called services, which can flexibly be combined in terms of a recommender construction kit. Different areas of an… (More)
Tracking people is a key technology for robots and intelligent systems in human environments. Many person detectors, filtering methods and data association algorithms for people tracking have been proposed in the past 15+ years in both the robotics and computer vision communities, achieving decent tracking performances from static and mobile platforms in… (More)
Understanding social context is an important skill for robots that share a space with humans. In this paper, we address the problem of recognizing gender, a key piece of information when interacting with people and understanding human social relations and rules. Unlike previous work which typically considered faces or frontal body views in image data, we… (More)
In this paper, we present a technique for adaptive generation of personalized route instructions based on the driver's knowledge of particular route sections. We evaluated the mechanism with two empirical studies, both attesting significant preference for the adaptively generated presentations over an established online service (Google Maps).
In this paper, we explain our notion of context, considering for instance membership in a group as context. We derive a model for context-adaptivity from the well-established one for user-adaptivity proposed by Jameson, and introduce context views as means for facilitating group-based work. Context views aim at identifying the most important elements within… (More)
Robots that cooperate and interact with humans require the capacity to detect and track people, analyze their behavior and understand human social relations and rules. A key piece of information for such tasks are human attributes like gender, age, hair or clothing. In this paper, we address the problem of recognizing such attributes in RGB-D data from… (More)