Sakarya, Ufuk
In this paper, we propose a weighted undirected graph-based video scene detection method. The method is based on the idea of using the complete information of the graph. For this aim, each shot is represented by a vertex on the graph. Edge weights among vertices are evaluated by using spatial and temporal similarities of shots. Only a single video scene boundary which has the highest probability to be the correct one is determined and this scene boundary information is also used as a clue in the next steps. A tree-based peeling strategy is proposed to determine the boundaries of the remaining scenes. In order to test our graph-based video scene detection method, we used DVD chapters' information and promising results were obtained when compared to the results of the similar work presented in literature.


A Graph-Based Approach for Video Scene Detection
Sakarya, Ufuk; Telatar, Zjya (2008-04-22)
In this paper, a graph-based method for video scene detection is proposed. The method is based on a weighted undirected graph. Each shot is a vertex on the graph. Edge weights among the vertices are evaluated by using spatial and temporal similarities of shots. By using the complete information of the graph, a set of the vertices mostly similar to each other and dissimilar to the others is detected. Temporal continuity constraint is achieved on this set. This set is the first detected video scene. The verti...
Özdemir, Okan Bilge; Soydan, Hilal; Çetin, Yasemin; Duzgun, Sebnem (2016-07-15)
This paper presents a vegetation detection application with semi-supervised target detection using hyperspectral unmixing and segmentation algorithms. The method firstly compares the known target spectral signature from a generic source such as a spectral library with each pixel of hyperspectral data cube employing Spectral Angle Mapper (SAM) algorithm. The pixel(s) with the best match are assumed to be the most likely target vegetation locations. The regions around these potential target locations are furt...
From Ramp Discontinuities to Segmentation Tree
Akbaş, Emre (2009-09-27)
This paper presents a new algorithm for low-level multiscale segmentation of images. The algorithm is designed to detect image regions regardless of their shapes, sizes, and levels of interior homogeneity, by doing a multiscale analysis without assuming any prior models of region geometry. As in previous work, a region is modeled as a homogeneous set of connected pixels surrounded by ramp discontinuities. A new transform, called the ramp transform, is described, which is used to detect ramp discontinuities ...
Exploitation of multi-camera configurations for visual surveillance
Akman, Oytun; Alatan, Abdullah Aydın; Çiloğlu, Tolga (2008-06-20)
In this paper, we propose novel methods for background modeling, occlusion. handling and event recognition by using multi-camera configurations. Homography-related positions are utilized to construct a mixture of multivariate Gaussians to generate a background model for each pixel of the reference camera. Occlusion handling is achieved by generation of the top-view via trifocal tensors, as a result of matching over-segmented regions instead of pixels. The resulting graph is segmented into objects after dete...
Graph-based multilevel temporal segmentation of scripted content videos
Sakarya, Ufuk; TELATAR, ZİYA (2007-06-13)
This paper concentrates on a graph-based multilevel temporal segmentation method for scripted content videos. In each level of the segmentation, a similarity matrix of frame strings, which are series of consecutive video frames, is constructed by using temporal and spatial contents of frame strings. A strength factor is estimated for each frame string by using a priori information of a scripted content. According to the similarity matrix reevaluated from a strength function derived by the strength factors, ...
Citation Formats
U. Sakarya and Z. TELATAR, “VIDEO SCENE DETECTION USING DOMINANT SETS,” 2008, p. 73, Accessed: 00, 2020. [Online]. Available: