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

In this paper, two essential problems that belong to language parsing and have arisen from dialogue management are discussed and solved by implementing a variant of the well-known context-free parsing algorithm [1]. The first problem is the use of partly specified patterns, i.e., the use of wildcards in the right-hand-sides of the rewriting rules of a context-free grammar. The second one is the use of priority patterns, i.e., the assignment of priority values to rewriting rules. These problems are not handled in the majority of the state-of-the-art dialogue systems. The proposed algorithm has been implemented in a dialogue system core application called CAML Core [7], that is used to implement dialogue systems in several domains like conversational and multimodal interfaces for help desk applications, and chat bots.

/pdf/partly-specified-priority-patterns-in-natural-language-3euu87pq3q.pdf

Partly-Specified Priority Patterns in Natural Language Parsing within Dialogue Systems

This paper presents a simulation of an access control system that deals with the problem of access control and copyright protection for broadcasted image-related services. The services that concentrate our interest include mainly Pay-TV, but also the existing and forthcoming multimedia services which are expected to share the same channels as digital TV for their diffusion in the future. We assume that these services have the basic characteristic of interactivity, which implies the existence of a return channel for the users to the service providers. The simulation is concentrated on the basic operations provided by the system, that make it flexible and, at the same time, make possible or help the access control and the billing of the services.

Simulation of an access control system for image-related services

A Viterbi algorithm for image edge detection

A scene change detection method is presented in this paper, which analyzes both auditory and visual information sources and accounts for their inter-relations and coincidence to semantically identify video scenes. Audio analysis focuses on the segmentation of the audio source into three types of semantic primitives, i.e. silence, speech and music. Further processing on speech segments aims at locating speaker change instants. Video analysis attempts to segment the video source into shots, without the segmentation being affected by camera pans, zoom-ins/outs or significantly high object motion. Results from single source segmentation are in some cases suboptimal. Audio-visual interaction achieves to either enhance single source findings or extract high level semantic information. The aim of this paper is to identify semantically meaningful video scenes by exploiting the temporal correlations of both sources based on the observation that semantic changes are characterized by significant changes in both information sources. Experimentation has been carried on a real TV serial sequence composed of many different scenes with plenty of commercials appearing in-between. The results are proven to be rather promising.

Scene Change Detection Based on Audio-Visual Analysis and Interaction

This paper addresses the problem of compensating for variable recording conditions such as changes in illumination, scale differences, and varying face position It is well known that the performance of any face authentication/recognition algorithm deteriorates significantly in the presence of the aforementioned conditions as well as the expression variations The use of simple and powerful pre-processing techniques aiming at compensating for variable recording conditions prior to the application of any authentication algorithm is proposed It is shown that such an approach overcomes indeed the image variations and guarantees an almost stable performance for the Morphological Dynamic Link Architecture developed within the European research project M2VTS

Ioannis Pitas

Papers

Partly-Specified Priority Patterns in Natural Language Parsing within Dialogue Systems

Simulation of an access control system for image-related services

A Viterbi algorithm for image edge detection

Scene Change Detection Based on Audio-Visual Analysis and Interaction

Compensating for variable recording conditions in frontal face authentication algorithms