There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past several years. At least two reasons account for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible technologies after 30 years of research. Even though current machine recognition systems have reached a certain level of maturity, their success is limited by the conditions imposed by many real applications. For example, recognition of face images acquired in an outdoor environment with changes in illumination and/or pose remains a largely unsolved problem. In other words, current systems are still far away from the capability of the human perception system.This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition, relevant topics such as psychophysical studies, system evaluation, and issues of illumination and pose variation are covered.

Face recognition: A literature survey

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.

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Detecting faces in images: a survey

The goal of the following analysis is to estimate the computational complexity of the Voronoi tessellation of an image performed with an algorithm based on mathematical morphology. The morphological dilation operation is used to implement a set of distance functions (distance transformations) with a variety of structuring elements that approximate distance metrics, such as the Euclidean, city block and chessboard distances. The analysis has been performed for 2-D morphological Voronoi tessellation.

Performance Analysis of a Morphological Voronoi Tessellation Algorithm

The computation of cyclic convolutions in Galois fields is an integral part of coding theory and formulation as well as of many signal processing applications. In this paper, we introduce a method for the computation of such convolutions that minimizes, in theory, the computational complexity of the algorithm. We also propose special-purpose computer architecture schemes for the efficient realization of the algorithm, and in general, for efficient calculation of convolutions in Galois fields.

Algorithms and structures for convolutions over Galois fields

Algorithms for the reduction of the input-output operations in the calculation of the two-dimensional Discrete Fourier transform

In this paper, a new nonlinear subspace learning technique for class-specific data representation based on an optimized class representation is described. An iterative optimization scheme is formulated where both the optimal nonlinear data projection and the optimal class representation are determined at each optimization step. This approach is tested on human face and action recognition problems, where its performance is compared with that of the standard class-specific subspace learning approach, as well as other nonlinear discriminant subspace learning techniques. Experimental results denote the effectiveness of this new approach, since it consistently outperforms the standard one and outperforms other nonlinear discriminant subspace learning techniques in most cases.

/pdf/class-specific-nonlinear-subspace-learning-based-on-c6yjraas8b.pdf

Class-specific nonlinear subspace learning based on optimized class representation

Active contour (snake) approaches have been proved to be efficient tools to extract object boundary precisely. One drawback of these methods is that state-of-the-art snake algorithms are usually computationally expensive. To overcome this difficulty, one approach is to reduce spatial resolution to make snake iteration faster. The disadvantage of this method is that the reduction of resolution ignores image content which may lead to losing useful image data. In this paper we propose a snake iteration method on quadtree representations derived from the image. In this way we can reduce resolution in a special and adaptive way. Once the iteration is finished on the sparse quadtree grid, final adjustments can be made by performing pixelwise snake iteration steps.

Ioannis Pitas

Papers

Performance Analysis of a Morphological Voronoi Tessellation Algorithm

Algorithms and structures for convolutions over Galois fields

Algorithms for the reduction of the input-output operations in the calculation of the two-dimensional Discrete Fourier transform

Class-specific nonlinear subspace learning based on optimized class representation

Content Adaptive Heterogeneous Snakes