Uros Damnjanovic

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In this paper, the method used for Rushes Summarization task by the COST 292 consortium is reported. The approach proposed this year differs significantly from the one proposed in the previous years because of the introduction of new processing steps, like repetition detection in scenes. The method starts with junk frames removal and follows with clustering(More)
In this paper, the method used for Rushes Summarization task by the COST 292 consortium is reported. The approach proposed this year differs significantly from the one proposed in the previous years because of the introduction of new processing steps, like repetition detection in scenes. The method starts with junk frames removal and follows with clustering(More)
Daily increase in the number of available video material resulted in significant research efforts for development of advanced content management systems. First step towards the semantic based video indexing and retrieval is a detection of elementary video structures. In this paper we present the algorithm for finding shot boundaries by using spectral(More)
The target of surveillance summarization is to identify high-value information events in a video stream and to present it to a user. In this paper we present surveillance summarization approach using detection and clustering of important events. Assuming that events are main source of energy change between consecutive frames set of interesting frames is(More)
In this paper, we give an overview of the four tasks submitted to TRECVID 2007 by COST292. In shot boundary (SB) detection task, four SB detectors have been developed and the results are merged using two merging algorithms. The framework developed for the high-level feature extraction task comprises four systems. The first system transforms a set of(More)
In this paper, we give an overview of the four tasks submitted to TRECVID 2008 by COST292. The high-level feature extraction framework comprises four systems. The first system transforms a set of low-level descriptors into the semantic space using Latent Semantic Analysis and utilises neural networks for feature detection. The second system uses a(More)
Decision-making is a fundamental part of digital objects production in the field of digital heritage. We present in this paper our efforts on developing an application that will enable easy documentation of the decision-making processes, and provide access to digital objects used in various stages of the process. Our application is built on top of a data(More)
Over the last few years spectral clustering has emerged as a powerful model for data partitioning and segmentation. Spectral clustering techniques use eigenvalues and eigenvectors of the matrix representation of a suitable graph representing the original data. In this paper a new spectral clustering method is proposed: the asymmetric cut. It allows(More)