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facial-feature-extraction
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Three-dimensional modular discriminant analysis (3DMDA): A new feature extraction approach for face recognition
, Article Computers and Electrical Engineering ; Volume 37, Issue 5 , 2011 , Pages 811-823 ; 00457906 (ISSN) ; Manzuri Shalmani, M. T ; Sharif University of Technology
Abstract
In this paper, we present a novel multilinear algebra based feature extraction approach for face recognition which preserves some implicit structural or locally-spatial information among elements of the original images. We call this method three-dimensional modular discriminant analysis (3DMDA). Our approach uses a new data model called third-order tensor model (3TM) for representing the face images. In this model, each image is partitioned into the several equal size local blocks, and the local blocks are combined to represent the image as a third-order tensor. Then, a new optimization algorithm called direct mode (d-mode) is introduced for learning three optimal projection axes. Extensive...
A real-time color-independent method for multiple fces tracking
, Article 6th IEEE International Conference on Cognitive Informatics, ICCI 2007, Lake Tahoe, CA, 6 August 2007 through 8 August 2007 ; October , 2007 , Pages 99-105 ; 1424413273 (ISBN); 9781424413270 (ISBN) ; Manzuri Shalmani, M. T ; Jamalian, A. H ; Sefidpour, A. R ; Sharif University of Technology
2007
Abstract
In this paper, we describe a real-time Gradient-based Multiple Faces Tracking (GMFT) algorithm in complex background. In GMFT method first faces are detected by combination of morphological facial feature extraction and gradient-based edge detection methods. After a face is reliably detected, it is tracked over time with a novel real-time algorithm. The algorithm has been implemented and tested under a wide range of real-world conditions. The resulting system runs in real-time on a standard PC, being robust to face scale variations, rotations in depth, and fast changes in subject/camera position. It has consistently provided performance which satisfies the following requirements: 1) able to...
Towards MPEG4 compatible face representation via hierarchical clustering-based facial feature extraction
, Article ISCI 2011 - 2011 IEEE Symposium on Computers and Informatics ; 2011 , Pages 436-441 ; 9781612846903 (ISBN) ; Mosleh, M ; Sharif University of Technology
Abstract
Multi-view imaging and display systems has taken a divide and conquer approach to 3D sensing and visualization. We aim to make more reliable and robust automatic feature extraction and natural 3D feature construction from 2D features detected on a pair of frontal and profile view face images. We propose several heuristic algorithms to minimize possible errors introduced by prevalent imperfect orthogonal condition and non-coherent luminance trying to address the problems incurred with illumination discrepancies on common surface points in accommodation of multi-views. In our approach, we first extract the 2D features that are visible to both cameras in both views. Then, we estimate the...
A new incremental face recognition system
, Article 2007 4th IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS, Dortmund, 6 September 2007 through 8 September 2007 ; 2007 , Pages 335-340 ; 1424413486 (ISBN); 9781424413485 (ISBN) ; Ghavami, A ; Abrishami Moghaddam, H ; Sharif University of Technology
2007
Abstract
In this paper, we present new adaptive linear discriminant analysis (LDA) algorithm and apply them for adaptive facial feature extraction. Adaptive nature of the proposed algorithm is advantageous for real world applications in which one confronts with a sequence of data such as online face recognition and mobile robotics. Application of the new algorithm on feature extraction from facial image sequences is given in three steps: i) adaptive image preprocessing, ii) adaptive dimension reduction and iii) adaptive LDA feature estimation. Steps 1 and 2 are done simultaneously and outputs of stage 2 are used as a sequence of inputs for stage3. The proposed system was tested on Yale and PIE face...