Nikolaos D. Doulamis

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— An adaptive algorithm for extracting foreground objects from background in videophone or videoconference applications is presented in this paper. The algorithm uses a neural network architecture that classifies the video frames in regions-of-interest (ROI) and non-ROI areas, also being able to automatically adapt its performance to scene changes. The(More)
Grid technology is widely emerging. Still, there is an eminent shortage of real Grid users, mostly due to the lack of a " critical mass " of widely deployed and reliable higher-level Grid services, tailored to application needs. The GridLab project aims to provide fundamentally new capabilities for applications to exploit the power of Grid computing, thus(More)
A framework for video content representation is proposed in this paper for extracting limited, but meaningful, information of video data directly from MPEG compressed domain. First, the traditional frame-based representation is transformed to a feature-based one. Then, all features are gathered together using a fuzzy formulation and extraction of several(More)
In this paper, a fuzzy representation of visual content is proposed, which is useful for the new emerging multimedia applications, such as content-based image indexing and retrieval, video browsing and summarization. In particular, a multidimensional fuzzy histogram is constructed for each video frame based on a collection of appropriate features, extracted(More)
A novel approach is presented in this paper for improving the performance of neural-network classifiers in image recognition, segmentation, or coding applications, based on a retraining procedure at the user level. The procedure includes: 1) a training algorithm for adapting the network weights to the current condition; 2) a maximum a posteriori (MAP)(More)
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, an efficient video content representation is proposed using optimal extraction of characteristic frames and scenes. This representation, apart from providing browsing capabilities to digital video databases, also allows more efficient content-based queries and indexing. For performing the frame/scene extraction, a feature vector formulation(More)