Over the last several years, major efforts have been made to develop methods for extracting information from audiovisual 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 audiovisual system or may be autonomous, as for example in the case of an audio recording stored digitally on disk. Our goal was to first develop a system for segmentation of the audio signal, and then classification into one of two main categories: speech or music. Among the system's requirements are its processing speed and its ability to function in a real-time environment with a small responding delay. Because of the restriction to two classes, the characteristics that are extracted are considerably reduced and moreover the required computations are straightforward. Experimental results show that efficiency is exceptionally good, without sacrificing performance. Segmentation is based on mean signal amplitude distribution, whereas classification utilizes an additional characteristic related to the frequency. The classification algorithm may be used either in conjunction with the segmentation algorithm, in which case it verifies or refutes a music-speech or speech-music change, or autonomously, with given audio segments. The basic characteristics are computed in 20 ms intervals, resulting in the segments' limits being specified within an accuracy of 20 ms. The smallest segment length is one second. The segmentation and classification algorithms were benchmarked on a large data set, with correct segmentation about 97% of the time and correct classification about 95%.

Oil spill models are combined with bathymetric, meteorological, oceanographic, and geomorphological data to model a series of oil spill accidents in the Eastern Mediterranean Sea. A total of 104 oil spill simulations, computed for 11 different locations in the Levantine Basin, show that oil slicks will reach the coast of Cyprus in four (4) to seven (7) days in summer conditions. Oil slick trajectories are controlled by prevailing winds and current eddies. Based on these results, we support the use of chemical dispersants in the very few hours after large accidental oil spills. As a corollary, we show shoreline susceptibility to vary depending on: a) differences in coastline morphology and exposure to wave action, b) the existence of uplifted wave-cut platforms, coastal lagoons and pools, and c) the presence of tourist and protected environmental areas. Mitigation work should take into account the relatively high susceptibility of parts of the Eastern Mediterranean.

We present a key frames selection algorithm based on three iso-content principles (iso-content distance, iso-content error and iso-content distortion), so that the selected key frames are equidistant in video content according to the used principle. Two automatic approaches for defining the most appropriate number of key frames are proposed by exploiting supervised and unsupervised content criteria. Experimental results and the comparisons with existing methods from literature on large dataset of real-life video sequences illustrate the high performance of the proposed schemata.

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 subtrajectories, the following methodology is proposed. First, a novel global voting algorithm is performed, based on local density and trajectory similarity information. This method is applied for each segment of the trajectory, forming a local trajectory descriptor that represents line segment representativeness. The sequence of this descriptor over a trajectory gives the voting signal of the trajectory, where high values correspond to the most representative parts. Then, a novel segmentation algorithm is applied on this signal that automatically estimates the number of partitions and the partition borders, identifying homogenous partitions concerning their representativeness. Finally, a sampling method over the resulting segments yields the most representative subtrajectories in the MOD. Our experimental results in synthetic and real MOD verify the effectiveness of the proposed scheme, also in comparison with other sampling techniques.