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This paper introduces an algorithm for fast temporal segmentation of videos into shots. The proposed method detects abrupt and gradual transitions, based on the visual similarity of neighboring frames of the video. The descriptive efficiency of both local (SURF) and global (HSV histograms) descriptors is exploited for assessing frame similarity, while(More)
This paper provides an overview of the Social Event Detection (SED) task, which is organized as part of the MediaEval 2011 benchmarking activity. With the convergence between social networking and multimedia creation and distribution being experienced on a regular basis by hundreds of millions of people worldwide, this task examines how new or state of the(More)
Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step towards the reliable quantitative assessment of atherosclerosis. In this work, a fully automated technique for the detection of lumen and(More)
In this paper, an image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions. Low-level features describing the color, position, size and shape of the resulting regions are extracted and are automatically(More)
—A novel unsupervised video object segmentation algorithm is presented, aiming to segment a video sequence to objects: spatiotemporal regions representing a meaningful part of the sequence. The proposed algorithm consists of three stages: initial segmentation of the first frame using color, motion, and position information, based on a variant of the(More)
A learning approach to knowledge-assisted image analysis and classification is proposed that combines global and local information with explicitly defined knowledge in the form of an ontology. The ontology specifies the domain of interest, its subdomains, the concepts related to each subdomain as well as contextual information. Support vector machines(More)
This paper presents a GPU-assisted version of the LIB-SVM library for Support Vector Machines. SVMs are particularly popular for classification procedures among the research community, but for large training data the processing time becomes unrealistic. The modification that is proposed is porting the computation of the kernel matrix elements to the GPU, to(More)
The detection of lumen and media-adventitia borders in intravascular ultrasound (IVUS) images constitutes a necessary step for the quantitative assessment of atherosclerotic lesions. To date, most of the segmentation methods reported are either manual, or semi-automated, requiring user interaction at some extent, which increases the analysis time and(More)
—An approach to knowledge-assisted semantic video object detection based on a multimedia ontology infrastructure is presented. Semantic concepts in the context of the examined domain are defined in an ontology, enriched with qualitative technologies are used for knowledge representation in the RDF(S) metadata standard. Rules in F-logic are defined to(More)
—In this paper, a novel algorithm is presented for the real-time, compressed-domain, unsupervised segmentation of image sequences and is applied to video indexing and retrieval. The segmentation algorithm uses motion and color information directly extracted from the MPEG-2 compressed stream. An iterative rejection scheme based on the bilinear motion model(More)