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

Seismic migration is a technique widely used in seismic oil exploration for wavefield reconstruction and for imaging the geometrical distribution of the reflection surfaces within the Earth from the seismic data recorded on the Earth surface. These data are usually corrupted by noise (white noise, surface waves, multiple reflections, etc.) that degrades the result of the migration. Another factor which influences the migration is the inadequate knowledge of the distribution of the acoustic wave propagation velocity in the subsurface of the Earth. The authors use estimation theory techniques to find the MAP (maximum a posterior) estimate of the wave propagation velocity and the geometrical distribution of the subsurface reflector points. >

Bayesian estimation in seismic migration

Metrics based on mutual information and not resorting to ground truth data are proposed in this paper in order to measure tracking reliability under occlusion., The variations of the proposed metrics can be used as a quantitative estimate of changes in the tracking region, caused by occlusion, sudden movement or the deformation of the tracked object. The proposed metric was tested on an object tracking scheme using multiple feature point correspondences. Experimental results have shown that mutual information can effectively characterize object appearance and reappearance in many computer vision applications.

Information theory-based analysis of partial and total occlusion in object tracking

Hierarchical Word Clustering for Relevance Judgments in Information Retrieval

This paper presents a novel method for multichannel and color image equalization. The equalization can be performed on the three channels RGB simultaneously, by using the joint pdf. Alternatively, equalization at the HSI domain can be performed, in order to avoid changes in digital image hue. A parallel algorithm is proposed for color image histogram calculation and equalization.

Multichannel histogram equalization with applications in the hsi color space

This paper introduces a robust roll angle estimation algorithm, which is developed from our previously published work, where the roll angle was estimated from a dense subpixel disparity map by minimizing a global energy using golden section search algorithm. In this paper, to achieve greater computational efficiency, we utilize gradient descent to optimize the aforementioned global energy. The experimental results illustrate that the presented roll angle estimation method takes fewer iterations to achieve the same precision as the previous method.

Ioannis Pitas

Papers

Bayesian estimation in seismic migration

Information theory-based analysis of partial and total occlusion in object tracking

Hierarchical Word Clustering for Relevance Judgments in Information Retrieval

Multichannel histogram equalization with applications in the hsi color space

A Robust Roll Angle Estimation Algorithm Based on Gradient Descent