We face the problem of novelty detection from stream data, that is, the identification of new or unknown situations in an ordered sequence of objects which arrive on-line, at cons...
We have developed a multiagent robotic system including perception, cognition, and action components to function in a dynamicenvironment. The system involves the integration and c...
We propose a novel learning algorithm to detect moving pedestrians from a stationary camera in real-time. The algorithm learns a discriminative model based on eigenflow, i.e. the ...
We present an algorithm for multi-person tracking-bydetection
in a particle filtering framework. To address the
unreliability of current state-of-the-art object detectors, our
a...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...