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Object modeling for multicamera correspondence using fuzzy region color adjacency graphs
, Article 13th International Computer Society of Iran Computer Conference on Advances in Computer Science and Engineering, CSICC 2008, Kish Island, 9 March 2008 through 11 March 2008 ; Volume 6 CCIS , 2008 , Pages 637-644 ; 18650929 (ISSN); 3540899847 (ISBN); 9783540899846 (ISBN) ; Kasaei, S ; Sharif University of Technology
2008
Abstract
In this paper, a novel moving object modeling suitable for multicamera correspondence is introduced. Taking into consideration the color and motion features of foreground objects in each independent video stream, our method segments the existing moving objects and constructs a graph-based structure to maintain the relational information of each segment. Using such graph structures reduces our correspondence problem to a subgraph optimal isomorphism problem. The proposed method is robust against various resolutions and orientations of objects at each view. Our system uses the fuzzy logic to employ a human-like color perception in its decision making stage in order to handle color inconstancy...
K/K-Nearest Neighborhood criterion for improving locally linear embedding
, Article Proceedings of the 2009 6th International Conference on Computer Graphics, Imaging and Visualization: New Advances and Trends, CGIV2009, 11 August 2009 through 14 August 2009, Tianjin ; 2009 , Pages 392-397 ; 9780769537894 (ISBN) ; Moghaddam, H. A ; Babaie Zadeh, M ; Sharif University of Technology
Abstract
Spectral manifold learning techniques have recently found extensive applications in machine vision. The common strategy of spectral algorithms for manifold learning is exploiting the local relationships in a symmetric adjacency graph, which is typically constructed using k-nearest neighborhood (k-NN) criterion. In this paper, with our focus on locally linear embedding as a powerful and well-known spectral technique, shortcomings of k-NN for construction of the adjacency graph are first illustrated, and then a new criterion, namely k/K-nearest neighborhood (k/K-NN) is introduced to overcome these drawbacks. The proposed criterion involves finding the sparsest representation of each sample in...
K/K-nearest neighborhood criterion for improvement of locally linear embedding
, Article 13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009, Munster, 2 September 2009 through 4 September 2009 ; Volume 5702 LNCS , 2009 , Pages 808-815 ; 03029743 (ISSN); 3642037666 (ISBN); 9783642037665 (ISBN) ; Abrishami Moghaddam, H ; Babaie Zadeh, M ; Sharif University of Technology
2009
Abstract
Spectral manifold learning techniques have recently found extensive applications in machine vision. The common strategy of spectral algorithms for manifold learning is exploiting the local relationships in a symmetric adjacency graph, which is typically constructed using k -nearest neighborhood (k-NN) criterion. In this paper, with our focus on locally linear embedding as a powerful and well-known spectral technique, shortcomings of k-NN for construction of the adjacency graph are first illustrated, and then a new criterion, namely k/K-nearest neighborhood (k/K-NN) is introduced to overcome these drawbacks. The proposed criterion involves finding the sparsest representation of each sample in...
A novel Markov random field model based on region adjacency graph for T1 magnetic resonance imaging brain segmentation
, Article International Journal of Imaging Systems and Technology ; Volume 27, Issue 1 , 2017 , Pages 78-88 ; 08999457 (ISSN) ; Yousefi, S ; Manzuri Shalmani, M. T ; Sharif University of Technology
John Wiley and Sons Inc
2017
Abstract
Tissue segmentation in magnetic resonance brain scans is the most critical task in different aspects of brain analysis. Because manual segmentation of brain magnetic resonance imaging (MRI) images is a time-consuming and labor-intensive procedure, automatic image segmentation is widely used for this purpose. As Markov Random Field (MRF) model provides a powerful tool for segmentation of images with a high level of artifacts, it has been considered as a superior method. But because of the high computational cost of MRF, it is not appropriate for online processing. This article has proposed a novel method based on a proper combination of MRF model and watershed algorithm in order to alleviate...