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Two dimensional compressive classifier for sparse images
, 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 402-405 ; 9780769537894 (ISBN) ; Moghaddam, H. A ; Babaie Zadeh, M ; Sharif University of Technology
Abstract
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the information in the signal, with high probability. Following the success in signal reconstruction, compressive framework has recently proved useful in classification, particularly hypothesis testing. In this paper, conventional random projection scheme is first extended to the image domain and the key notion of concentration of measure is closely studied. Findings are then employed to develop a 2D compressive classifier (2D-CC) for sparse images. Finally, theoretical results are validated within a realistic...
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...
A novel hardware implementation for joint heart rate, respiration rate, and gait analysis applied to body area networks
, Article Proceedings - IEEE International Symposium on Circuits and Systems ; 2013 , Pages 1889-1892 ; 02714310 (ISSN) ; 9781467357609 (ISBN) ; Zamani, A. R ; Hallajian, M ; Ehsani, S. P ; Moghaddam, H. A ; Parsafar, A ; Shabany, M ; Sharif University of Technology
2013
Abstract
Continuous and remote monitoring of vital health-related and physical activity signs of a patient is one of the most important technology-oriented applications to monitor the health-care of ill individuals. In this paper, an innovative framework for a wireless Body Area Network (BAN) system, based on the IEEE 802.15.6 standard, with three types of sensors is proposed and implemented. These include Electrocardiogram (ECG), Force Sensitive Resistor (FSR) and Gyroscope. The proposed design is a novel implementation of an embedded system for the real-time processing and analyzing of the ECG signal, gait phases, and detection of the respiration rate from the ECG signal, by means of small...