Athanasios Voulodimos

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In this paper, we propose a novel online framework for behavior understanding, in visual workflows, capable of achieving high recognition rates in real-time. To effect online recognition, we propose a methodology that employs a Bayesian filter supported by hidden Markov models. We also introduce a novel readjustment framework of behavior recognition and(More)
In this paper we introduce the WR (Workflow Recognition) dataset. Recorded in the production line of a major automobile manufacturer, this dataset consists of sequences that depict workers executing industrial workflows. The heavy oc-clusions, outliers, the visually complicated background and the human-machinery interaction are among the factors that make(More)
— The emergence of cloud environments has made feasible the delivery of Internet-scale services by addressing a number of challenges such as live migration, fault tolerance and quality of service. However, current approaches do not tackle key issues related to cloud storage, which are of increasing importance given the enormous amount of data being produced(More)
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—In this work, we propose a framework for classifying structured human behavior in complex real environments, where problems such as frequent illumination changes and heavy occlusions are expected. Since target recognition and tracking can be very challenging, we bypass these problems by employing an approach similar to Motion History Images for feature(More)
In this paper we propose a method to enhance activity recognition in complex environments, where problems like occlusions, noise and illumination changes are present. In order to address the problems induced by the dependency on the camera's viewpoint, multiple cameras are commonly used in an endeavour to exploit redundancies. We initially examine the(More)
Camera based supervision is a critical part of event detection and analysis applications. However, visual tracking still remains one of the biggest challenges in the area of computer vision, although it has been extensively discussed during in the previous years. In this paper we propose a robust tracking approach based on object flow, which is a motion(More)
B ehavior recognition in video is a focal point of research in the computer vision, image processing, and multimedia communities. Driven by applications such as assistive technologies , security, intelligent transportation, and human-computer interaction, a considerable body of work targets hierarchical event detection , workflow monitoring, and structured(More)
Human behavior recognition and real world environments monitoring constitute challenging research problems rapidly gaining momentum over the last years. Methods for time series classification like the Hidden Markov Models have been employed in the past for similar tasks, however in many challenging cases they fail, since some behaviors are much more(More)