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1
Content available People tracking in video surveillance systems based on artificial intelligence
Nasry Abir, Ezzahout Abderrahmane, Omary Fouzia
Journal of Automation Mobile Robotics and Intelligent Systems
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2023
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Vol. 17, No. 1
59--68
EN
As security is one of the basic human needs, we need security systems that can prevent crimes from happen‐ ing. In general, surveillance videos are used to observe the environment and human behavior in a given location. However, surveillance videos can only be used to record images or videos, without additional information. There‐ fore, more advanced cameras are needed to obtain other additional information such as the position and move‐ ment of people. This research extracted this information from surveillance video footage using a person tracking, detection, and identification algorithm. The framework for these is based on deep learning algorithms, a popu‐ lar branch of artificial intelligence. In the field of video surveillance, person tracking is considered a challenging task. Many computer vision, machine learning, and deep learning techniques have been developed in recent years. The majority of these techniques are based on frontal view images or video sequences. In this work, we will compare some previous work related to the same topic.
2
Content available A New Proposal for Person Identication Based on the Dynamics of Typing : Preliminary Results
Buza K., Neubrandt D.
Theoretical and Applied Informatics
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2016
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Vol. 28, No. 1-2
1--12
EN
The availability of cheap and widely applicable person identification techniques is essential due to a wide-spread usage of online services. The dynamics of typing is characteristic to particular users, and users are hardly able to mimic the dynamics of typing of others. State-of-the-art solutions for person identification from the dynamics of typing are based on machine learning. The presence of hubs, i.e., few instances that appear as nearest neighbours of surprisingly many other instances, have been observed in various domains recently and hubness-aware machine learning approaches have been shown to work well in those domains. However, hubness has not been studied in the context of person identification yet, and hubnessaware techniques have not been applied to this task. In this paper, we examine hubness in typing data and propose to use ECkNN, a recent hubness-aware regression technique together with dynamic time warping for person identification. We collected time-series data describing the dynamics of typing and used it to evaluate our approach. Experimental results show that hubness-aware techniques outperform state-of-the-art time-series classifiers.
3
Content available remote Person identification system using an identikit picture of the suspect
Bobulski J, Kubanek M
Optica Applicata
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2012
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Vol. 42, nr 4
865--873
EN
The article presents a person identification system, which may work with an identikit picture. The identikit picture (sketch) is often used in practice as an investigative tool to search for the perpetrators of an unknown identity. With a portrait of the perpetrator of a crime, one may identify the criminal. When the face database for comparisons is large, this is labour-absorbing. With the help of a computer system of face identification, this process becomes quick and easy.
4
Content available remote Person identification based on iris image analysis with special emphasis on hardware implementation - statistical analysis
Grabowski K.
Zeszyty Naukowe. Elektryka / Politechnika Łódzka
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2011
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z. 123
67-75
EN
The paper presents main results of PhD dissertation concerning authentication systems based on the analysis of iris pattern. Two main threads of the work are presented: iris image segmentation and its influence on the feature extraction algorithm and methods of analysis of biometric system efficiency.
PL
W artykule przedstawiono główne rezultaty badań zawartych w rozprawie autora dotyczącej systemów uwierzytelniania osób na podstawie obrazu tęczówki oka. Zaprezentowano dwa główne wątki pracy doktorskiej: segmentacji obrazu tęczówki i jej wpływu na proces ekstrakcji cech oraz metod analizy wydajności biometrycznej systemów uwierzytelniania.
5
Content available remote Person identification based on iris image analysis with special emphasis on hardware implementation
Grabowski K.
Zeszyty Naukowe. Elektryka / Politechnika Łódzka
|
2010
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z. 122
13-18
EN
The paper presents main results of PhD dissertation concerning authentication systems based on the analysis of iris pattern. The work presents the possibility of computing hardware acceleration of this process.
PL
W artykule przedstawiono główne rezultaty badań zawartych w rozprawie autora dotyczącej systemów uwierzytelniania osób na podstawie obrazu tęczówki oka. Zaprezentowano wątek sprzętowej implementacji systemu uwierzytelniania 1:N przy użyciu układów FPGA i DSP.
6
Identyfikacja osób na podstawie wzoru tęczówki
Rachubiński M.
Studia Informatica
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2008
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Vol. 29, nr 2A
23-37
PL
W artykule zaprezentowano istniejące algorytmy rozpoznawania osób na podstawie tęczówki oka oraz przedstawiono nowy algorytm ekstrakcji cech tęczówki. Algorytm wykorzystuje transformatę falkową do analizy obrazu. Kod tęczówki wyznaczony jest za pomocą współczynników falkowych na bazie słownika wedgletów.
EN
This paper present existing algorithms for personal identification based on iris pattern and propose a new algorithm for iris feature extraction. The algorithm is based on texture analysis using wavelet transform. Iris code is generated using representation of the wavelet coefficients based on the wedgelet dictionary.
7
Content available remote Image processing methods in person identification applications - ear biometrics
Choraś M.
Przegląd Elektrotechniczny
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2005
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R. 81, nr 4
38-41
EN
The future of biometrics will surely lead to systems based on image analysis as the data acquisition is very simple and requires only cameras, scanners or sensors. More importantly such methods could be passive, which means that the user does not have to take active part in the whole process or, in fact, would not even know that the process of identification takes place. There are many possible data sources for human identification systems, but the physiological biometrics seem to have many advantages over methods based on human behaviour. The most interesting human anatomical parts for such passive, physiological biometrics systems based on images acquired from cameras are face and ear. Both of those methods contain large volume of unique features that allow to distinctively identify many users and will be surely implemented into efficient biometrics systems for many applications. The article presents ear biometrics and a novel geometrical method of feature extraction from ear images in order to perform human identification.
PL
W ostatnich latach odchodzi się od tradycyjnych sposobów identyfikacji osób, a uznanie zyskują metody biometryczne oparte na przetwarzaniu obrazów. W artykule zaprezentowano metodę identyfikacji osób na podstawie cech ucha i przedstawiono algorytmy wydzielania cech z obrazów ucha. Uzyskane wyniki są porównywalne z wynikami identyfikacji innymi metodami biometrycznymi.
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