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Author

Ioannis Pitas

Other affiliations: University of Bristol, University of York, University of Toronto  ...read more
Bio: Ioannis Pitas is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Facial recognition system & Digital watermarking. The author has an hindex of 76, co-authored 795 publications receiving 24787 citations. Previous affiliations of Ioannis Pitas include University of Bristol & University of York.


Papers
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Proceedings ArticleDOI
20 Nov 2014
TL;DR: A new semantic framework within AVDP is proposed and examples of using AVDP to describe the results of analysis algorithms on stereo video and multichannel audio content are presented.
Abstract: In this paper, we propose a way of using the Audio-Visual Description Profile (AVDP) of the MPEG-7 standard for 2D or stereo video and multichannel audio content description. Our aim is to provide means of using AVDP in such a way, that 3D video and audio content can be correctly and consistently described. Since AVDP semantics do not include ways for dealing with 3D audiovisual content, a new semantic framework within AVDP is proposed and examples of using AVDP to describe the results of analysis algorithms on stereo video and multichannel audio content are presented.

1 citations

Proceedings ArticleDOI
19 Apr 1994
TL;DR: Simulation results clearly indicate that circular filters can be used effectively to remove noise when the estimation of color hue is of primary importance.
Abstract: Vector direction estimation can be very important in applications like hue color component filtering or motion direction estimation from noisy motion vector fields. Vector representation and manipulation in polar coordinates greatly facilitates the accomplishment of the previous task. Based on angular estimators of location, the authors introduce a number of "circular" filters, i.e. filters for angular input data. These filters include circular mean, median and a-trimmed mean filters. Emphasis is given to a circular median filter for which the approximate output pdf as well as other interesting properties are derived. The effectiveness of angular estimators of location in noise filtering is studied in simulations involving color images. Simulation results clearly indicate that circular filters can be used effectively to remove noise when the estimation of color hue is of primary importance. >

1 citations

Proceedings ArticleDOI
26 May 2014
TL;DR: A method is proposed that manipulates images in a manner that hinders face recognition by automatic recognition algorithms so that humans can identify the person or persons in a scene, while common classification algorithms fail to do so.
Abstract: In this paper, a method is proposed that manipulates images in a manner that hinders face recognition by automatic recognition algorithms. The purpose of this method, is to partly degrade image quality, so that humans can identify the person or persons in a scene, while common classification algorithms fail to do so. The approach used to achieve this involves the use of singular value decomposition (SVD). From experiments it can be concluded that, the method reduces the percentage of correct classification rate by over 90%. In addition, the final image is not degraded beyond recognition by humans.

1 citations

Proceedings ArticleDOI
01 Sep 2012
TL;DR: A novel person identification method exploiting human motion information by using their poses during action execution using Fuzzy Vector Quantization and Discriminant Learning is proposed.
Abstract: In this paper we propose a novel person identification method exploiting human motion information. Persons are described by using their poses during action execution. Identification process involves Fuzzy Vector Quantization and Discriminant Learning. In the case of multiple cameras used in the identification phase, single-view identification results combination is achieved by employing a Bayesian combination strategy. The proposed identification approach does not set the assumptions of known action class and number of capturing cameras in the identification phase. Experimental results on two publicly available video databases denote the effectiveness of the proposed approach.

1 citations

Proceedings ArticleDOI
22 May 1991
TL;DR: Two adaptive nonlinear filter structures are proposed which are based on linear combinations of order statistics and have the ability to incorporate constraints imposed on coefficients in order to permit location-invariant and unbiased estimation of a constant signal in the presence of additive white noise.
Abstract: Two adaptive nonlinear filter structures are proposed which are based on linear combinations of order statistics. These adaptive schemes are modifications of the standard LMS algorithm and have the ability to incorporate constraints imposed on coefficients in order to permit location-invariant and unbiased estimation of a constant signal in the presence of additive white noise. The convergence in the mean of the filter coefficients is proven. The proposed filters can adapt well to a variety of noise probability distributions ranging from short-tailed to long-tailed distributions. >

1 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: 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 …

33,785 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Abstract: 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.

6,384 citations

Journal ArticleDOI
TL;DR: In this article, the authors categorize and evaluate face detection algorithms and discuss relevant issues such as data collection, evaluation metrics and benchmarking, and conclude with several promising directions for future research.
Abstract: 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.

3,894 citations