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Background Modeling for Object Tracking
, M.Sc. Thesis Sharif University of Technology ; Kasaei, Shohreh (Co-Advisor)
Abstract
Nowadays, with high performance computers and progress in video recorder devices and their related technologies, price of these devices is being balanced and recording the videos is conventional now. Processing of these videos has been a challenge in industry and science. Control and surveillance of places such as airports and roads and reducing their sizes in memory are some of their research area. Usually one of the initial preprocesses of such applications specially the object tracking is background modeling and background subtraction. This preprocess has an essential effect on the other algorithms that process based on these processes’ results. If this section conducted with fewer...
3D Mosaicing Using Multiview Videos
, M.Sc. Thesis Sharif University of Technology ; Kasaei, Shohreh (Supervisor)
Abstract
In many applications of multi view 3D reconstruction, image mosaicing is one of the most important processes. Image mosaicing is the action of stitching some pictures of a scene so that a complete picture of the scene is constructed. The proposed method is such that for PTZ cameras by extracting features from frame, the homography matrix between frames will be computed. Then by converting plane coordinate into spherical coordinate, a complete picture of the scene will be constructed and forground will be removed. For fixed cameras sufficient corresponding points will be selected for computing the homography matrix between cameras. Using the homography, the frames without forground will be...
A novel vehicle tracking method with occlusion handling using longest common substring of chain-codes
, Article 2009 14th International CSI Computer Conference, CSICC 2009, Tehran, 20 October 2009 through 21 October 2009 ; 2009 , Pages 176-181 ; 9781424442621 (ISBN) ; Kasaei, S ; Sharif University of Technology
Abstract
Vehicle tracking is an essential requirement of any vision based Intelligent Transportation System for extracting different traffic parameters, efficiently. Handling inter-object occlusion is the most challenging part of tracking as a process of finding and following interested objects in a sequence of video frames. In this paper we present a system, based on code-book background model for motion segmentation and Kalman filter for tracking with a new approach for occlusion. This approach separates occluded vehicles based on longest common substring of chain codes. We use this tracking system to estimate some traffic parameters. Experimental results show the efficiency of the method. ©2009...
Sparse and low-rank recovery using adaptive thresholding
, Article Digital Signal Processing: A Review Journal ; Volume 73 , 2018 , Pages 145-152 ; 10512004 (ISSN) ; Marvasti, F ; Sharif University of Technology
Elsevier Inc
2018
Abstract
In this paper, we propose an algorithm for recovery of sparse and low-rank components of matrices using an iterative method with adaptive thresholding. In each iteration of the algorithm, the low-rank and sparse components are obtained using a thresholding operator. The proposed algorithm is fast and can be implemented easily. We compare it with the state-of-the-art algorithms. We also apply it to some applications such as background modeling in video sequences, removing shadows and specularities from face images, and image restoration. The simulation results show that the proposed algorithm has a suitable performance with low run-time. © 2017 Elsevier Inc
Low rank and sparse decomposition for image and video applications
, Article IEEE Transactions on Circuits and Systems for Video Technology ; Volume 30, Issue 7 , 2020 , Pages 2046-2056 ; Amini, A ; Marvasti, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
The matrix decomposing into a sum of low-rank and sparse components has found extensive applications in many areas including video surveillance, computer vision, and medical imaging. In this paper, we propose a new algorithm for recovery of low rank and sparse components of a given matrix. We have also proved the convergence of the proposed algorithm. The simulation results with synthetic and real signals such as image and video signals indicate that the proposed algorithm has a better performance with lower run-time than the conventional methods. © 1991-2012 IEEE
HMM-based phrase-independent i-vector extractor for text-dependent speaker verification
, Article IEEE/ACM Transactions on Audio Speech and Language Processing ; Volume 25, Issue 7 , 2017 , Pages 1421-1435 ; 23299290 (ISSN) ; Sameti, H ; Burget, L ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
The low-dimensional i-vector representation of speech segments is used in the state-of-the-art text-independent speaker verification systems. However, i-vectors were deemed unsuitable for the text-dependent task, where simpler and older speaker recognition approaches were found more effective. In this work, we propose a straightforward hidden Markov model (HMM) based extension of the i-vector approach, which allows i-vectors to be successfully applied to text-dependent speaker verification. In our approach, the Universal Background Model (UBM) for training phrase-independent i-vector extractor is based on a set of monophone HMMs instead of the standard Gaussian Mixture Model (GMM). To...
MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments
, Article PLoS Computational Biology ; Volume 18, Issue 6 , 2022 ; 1553734X (ISSN) ; Modegh, R. G ; Rabiee, H. R ; Sarbandi, E. R ; Rezaie, N ; Tam, K. T ; Forrest, A. R. R ; Sharif University of Technology
Public Library of Science
2022
Abstract
Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly...