Costas Panagiotakis

Learn More
Over the last years major e orts have been made to develop methods for extracting information from audio-visual media, in order that they may be stored and retrieved in databases automatically, based on their content. In this work we deal with the characterization of an audio signal, which may be part of a larger audio-visual system or may be autonomous, as(More)
In this paper, we propose an efficient clustering algorithm that has been applied to the microaggregation problem. The goal is to partition N given records into clusters, each of them grouping at least K records, so that the sum of the within-partition squared error (SSE) is minimized. We propose a successive Group Selection algorithm that approximately(More)
We propose a general purpose image segmentation framework, which involves feature extraction and classification in feature space, followed by flooding and merging in spatial domain. Region growing is based on the computed local measurements and distances from the distribution of features describing the different classes. Using the properties of the label(More)
Moving Object Databases (MOD), although ubiquitous, still call for methods that will be able to understand, search, analyze, and browse their spatiotemporal content. In this paper, we propose a method for trajectory segmentation and sampling based on the representativeness of the (sub)trajectories in the MOD. In order to find the most representative(More)
We present a model-based, top-down solution to the problem of tracking the 3D position, orientation and full articulation of the human body from markerless visual observations obtained by two synchronized RGBD cameras. Inspired by recent advances to the problem of model-based hand tracking Oikonomidis et al. (Efficient Model-based 3D Tracking of Hand(More)
This paper focuses on human behavior recognition where the main problem is to bridge the semantic gap between the analogue observations of the real world and the symbolic world of human interpretation. For that, a fusion architecture based on the Transferable Belief Model framework is proposed and applied to action recognition of an athlete in video(More)
In this paper, we propose a method for the automatic 4 identification of P -phase arrival based on the distribution of local 5 maxima (LM) in earthquake seismograms. The method efficiently 6 combines energy and frequency characteristics of the LM distri7 bution (LMD). The P detection is mainly based on the energy of 8 a seismic event in the case the(More)
The main goal of the proposed method is to select from a video the most “significant” frames in order to broadcast, without apparent loss of content by decreasing the potential distortion criterion. Initially, the video is divided into shots and the number of synopsis frames per shot is computed based on a criterion that takes into account the visual(More)