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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
10 Dec 2002
TL;DR: An analysis indicates whether bagging, a method for generating multiple versions of a classifier from bootstrap samples of a training set, and combining their outcomes by majority voting, is expected to improve the accuracy of the classifier.
Abstract: In this paper we study the stability of support vector machines in face detection by decomposing their average prediction error into the bias, variance, and aggregation effect terms. Such an analysis indicates whether bagging, a method for generating multiple versions of a classifier from bootstrap samples of a training set, and combining their outcomes by majority voting, is expected to improve the accuracy of the classifier. We estimate the bias, variance, and aggregation effect by using bootstrap smoothing techniques when support vector machines are applied to face detection in the AT & T face database and we demonstrate that support vector machines are stable classifiers. Accordingly, bagging is not expected to improve their face detection accuracy.

7 citations

Book ChapterDOI
01 Jan 2011
TL;DR: The description of the human centered interface specifications, research and implementations for systems geared towards the well-being of aged people, and affective interfaces that can help assessing the emotional status of the elderly are described.
Abstract: Assisted living has a particular social importance in most developed societies, due to the increased life expectancy of the general population and the ensuing ageing problems. It has also importance for the provision of improved home care in cases of disabled persons or persons suffering from certain diseases that have high social impact. This paper is primarily focused on the description of the human centered interface specifications, research and implementations for systems geared towards the well-being of aged people. Two tasks will be investigated in more detail: a) nutrition support to prevent undernourishment/malnutrition and dehydration, and b) affective interfaces that can help assessing the emotional status of the elderly. Such interfaces can be supported by ambient intelligence and robotic technologies.

7 citations

Journal ArticleDOI
01 Dec 2004
TL;DR: Metrics measuring tracking reliability under occlusion that are based on mutual information and do not resort to ground truth data are proposed and tested on an object tracking scheme using multiple feature point correspondences.
Abstract: Metrics measuring tracking reliability under occlusion that are based on mutual information and do not resort to ground truth data are proposed. Metrics for both the initialisation of the region to be tracked as well as for measuring the performance of the tracking algorithm are presented. The metrics variations may be interpreted as a quantitative estimate of changes in the tracking region due to occlusion, sudden movement or deformation of the tracked object. Performance metrics based on the Kullback -Leibler distance and normalised correlation were also added for comparison purposes. The proposed approach was tested on an object tracking scheme using multiple feature point correspondences. Experimental results have shown that mutual information can effectively characterise object appearance and reappearance in many computer vision applications.

7 citations

Book ChapterDOI
23 Oct 2016
TL;DR: A compact framework is presented for the description and representation of videos depicting human activities, with the goal of enabling automated large-volume video summarization for semantically meaningful key-frame extraction.
Abstract: A compact framework is presented for the description and representation of videos depicting human activities, with the goal of enabling automated large-volume video summarization for semantically meaningful key-frame extraction. The framework is structured around the concept of per-frame visual word histograms, using the popular Bag-of-Features approach. Three existing image descriptors (histogram, FMoD, SURF) and a novel one (LMoD), as well as a component of an existing state-of-the-art activity descriptor (Dense Trajectories), are adapted into the proposed framework and quantitatively compared against each other, as well as against the most common video summarization descriptor (global image histogram), using a publicly available annotated dataset and the most prevalent video summarization method, i.e., frame clustering. In all cases, several image modalities are exploited (luminance, hue, edges, optical flow magnitude) in order to simultaneously capture information about the depicted shapes, colors, lighting, textures and motions. The quantitative evaluation results indicate that one of the proposed descriptors clearly outperforms the competing approaches in the context of the presented framework.

7 citations

Proceedings ArticleDOI
07 Jun 1999
TL;DR: The results obtained indicate that the proposed approach overcomes the image variations and stabilizes the performance of the authentication algorithm.
Abstract: In this paper, morphological elastic graph matching is applied to frontal face authentication on databases collected either under optimal conditions or during real-world tests (i.e., access-control to buildings or tele-services via Internet in a typical office environment). It is demonstrated that the morphological elastic graph matching achieves a very low equal error rate on databases collected under optimal conditions. However its performance deteriorates in real-world experiments. The compensation for variable recording conditions, such as changes in illumination, scale differences and varying face position prior to the application of morphological elastic matching is proposed. The results obtained indicate that the proposed approach overcomes the image variations and stabilizes the performance of the authentication algorithm.

7 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