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.

/pdf/detecting-faces-in-images-a-survey-4yhbbns6mr.pdf

Detecting faces in images: a survey

Digital watermarking methods have been proposed for various purposes and especially for copyright protection of multimedia data. The digital watermark is embedded in a digital signal or an image and must be unrecognizable by unauthorized persons and detectable only by the legal copyright owner. We use toral automorphisms as chaotic 2-D integer vector generators in order to manipulate digital image watermarking. We propose also an embedding algorithm which provides robustness under filtering and compression.

Applications of toral automorphisms in image watermarking

The use of nonlinear means in image processing is introduced. The properties of these means in the presence of different types of noise are investigated. It is shown that nonlinear filters based on these means behave well for both additive and impulse noise. Their performance in the presence of signal dependent noise is satisfactory. They preserve the edges better than linear filters, and they reject the noise better than median filters.

Nonlinear mean filters in image processing

In this paper a new multi-view/3D human action/interaction database is presented. The database has been created using a convergent eight camera setup to produce high definition multi-view videos, where each video depicts one of eight persons performing one of twelve different human motions. Various types of motions have been recorded, i.e., scenes where one person performs a specific movement, scenes where a person executes different movements in a succession and scenes where two persons interact with each other. Moreover, the subjects have different body sizes, clothing and are of different sex, nationalities, etc.. The multi-view videos have been further processed to produce a 3D mesh at each frame describing the respective 3D human body surface. To increase the applicability of the database, for each person a multi-view video depicting the person performing sequentially the six basic facial expressions separated by the neutral expression has also been recorded. The database is freely available for research purposes.

/pdf/the-i3dpost-multi-view-and-3d-human-action-interaction-10qm0o90rz.pdf

The i3DPost Multi-View and 3D Human Action/Interaction Database

Recognition of human faces out of still images or image sequences is a research field of fast increasing interest. At first, facial regions and facial features like eyes and mouth have to be extracted. In the present paper we propose an approach that copes with problems of these first two steps. We perform face localization based on the observation that human faces are characterized by their oval shape and skin-color, also in the case of varying light conditions. For that we segment faces by evaluating shape and color (HSV) information. Then face hypotheses are verified by searching for facial features inside of the face-like regions. This is done by applying morphological operations and minima localization to intensity images.

Face localization and facial feature extraction based on shape and color information

Multivariate data ordering and its use in color image filtering are presented. Several of the filters presented are extensions of the single-channel filters based on order statistics. The statistical analysis of the marginal order statistics is presented for the p-dimensional case. A family of multichannel filters based on multivariate data ordering, such as the marginal median, the vector median, the marginal alpha -trimmed mean, and the multichannel modified trimmed mean filter, is described in detail. The performance of the marginal median and the vector median filters in impulsive noise filtering is investigated. Simulation examples of the filters under study are described. >

Ioannis Pitas

Papers

Applications of toral automorphisms in image watermarking

Nonlinear mean filters in image processing

The i3DPost Multi-View and 3D Human Action/Interaction Database

Face localization and facial feature extraction based on shape and color information

Multivariate ordering in color image filtering