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

Face detection is a key problem in building automated systems that perform face recognition A very attractive approach for face detection is based on multiresolution images (also known as mosaic images) Motivated by the simplicity of this approach, a rule-based face detection algorithm in frontal views is developed that extends the work of G Yang and TS Huang (see Pattern Recognition, vol27, no1, p53-63, 1994) The proposed algorithm has been applied to frontal views extracted from the European ACTS M2VTS database that contains the videosequences of 37 different persons It has been found that the algorithm provides a correct facial candidate in all cases However, the success rate of the detected facial features (eg eyebrows/eyes, nostrils/nose, and mouth) that validate the choice of a facial candidate is found to be 865% under the most strict evaluation conditions

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Rule-based face detection in frontal views

A technique for decomposing a binary shape into a union of simple binary shapes is presented. The decomposition is shown to be unique and invariant to translation, rotation, and scaling. The techniques used in the decomposition are based on mathematical morphology. The shape description produced can be used in object recognition and in binary image coding. >

Morphological shape decomposition

Most of the watermarking schemes that have been proposed until now employ a correlation detector (matched filter). The current paper proposes a new detector scheme that can be applied in the case of additive watermarking in the DCT (discrete cosine transform) or DWT (discrete wavelet transform) domain. Certain properties of the probability density function of the coefficients in these domains are exploited. Thus, an asymptotically optimal detector is constructed based on well known results of the detection theory. Experimental results prove the superiority of the proposed detector over the correlation detector.

Asymptotically optimal detection for additive watermarking in the DCT and DWT domains

An analysis of facial expression recognition under partial facial image occlusion

The authors present a new approach for automatically segmentation and tracking of faces in color images. Segmentation of faces is performed by evaluating color and shape information. First, skin-like regions are determined based on the color attributes hue and saturation. Then regions with elliptical shape are selected as face hypotheses. They are verified by searching for facial features in their interior. After a face is reliably detected it is tracked over time. Tracking is realized by using an active contour model. The exterior forces of the snake are defined based on color features. They push or pull snaxels perpendicular to the snake. Results for tracking are shown for an image sequence consisting of 150 frames.

Ioannis Pitas

Papers

Rule-based face detection in frontal views

Morphological shape decomposition

Asymptotically optimal detection for additive watermarking in the DCT and DWT domains

An analysis of facial expression recognition under partial facial image occlusion

Segmentation and tracking of faces in color images