QUALITY EVALUATION OF STEREOSCOPIC VIDEOS USING DEPTH MAP SEGMENTATION

2011-09-09
Sarikan, Selim S.
Olgun, Ramazan F.
Akar, Gözde
This paper presents a new quality evaluation model for stereoscopic videos using depth map segmentation. This study includes both objective and subjective evaluation. The goal of this study is to understand the effect of different depth levels on the overall 3D quality. Test sequences with different coding schemes are used. The results show that overall quality has a strong correlation with the quality of the background, where disparity is smaller relative to the foreground. The results also showed that content type is an important factor in determining the visual quality. While depth segmentation gives information related to 3D perception, additional work is required to develop an objective metric.

Suggestions

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, ...
Multi-image region growing for integrating disparity maps
Leloglu, UĞUR MURAT; Halıcı, Uğur (1999-01-01)
In this paper, a multi-image region growing algorithm to obtain planar 3-D surfaces in the object space from multiple dense disparity maps, is presented. A surface patch is represented by a plane equation and a set of pixels in multiple images. The union of back projections of all pixels in the set onto the infinite plane, forms the surface patch. Thanks to that hybrid representation of planar surfaces, region growing (both region aggregation and region merging) is performed on all images simultaneously. Pl...
Image segmentation with unified region and boundary characteristics within recursive shortest spanning tree
Esen, E.; Alp, Y. K. (2007-06-13)
The lack of boundary information in region based image segmentation algorithms resulted in many hybrid methods that integrate the complementary information sources of region and boundary, in order to increase the segmentation performance. In compliance with this trend, we propose a novel method to unify the region and boundary characteristics within the canonical Recursive Shortest Spanning Tree algorithm. The main idea is to incorporate the boundary information in the distance metric of RSST with minor cha...
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...
REGION-BASED IMAGE SEGMENTATION VIA GRAPH CUTS
Cigla, Cevahir; Alatan, Abdullah Aydın (2008-01-01)
A graph theoretic color image segmentation algorithm is proposed, in which the popular normalized cuts image segmentation method is improved with modifications on its graph structure. The image is represented by a weighted undirected graph, whose nodes correspond to over-segmented regions, instead of pixels, that decreases the complexity of the overall algorithm. In addition, the link weights between the nodes are calculated through the intensity similarities of the neighboring regions. The irregular distri...
Citation Formats
S. S. Sarikan, R. F. Olgun, and G. Akar, “QUALITY EVALUATION OF STEREOSCOPIC VIDEOS USING DEPTH MAP SEGMENTATION,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54593.