People search based on attributes description provided by an eyewitness for video surveillance applications

Frikha, Mayssa; Fendri, Emna; Hammami, Mohamed

doi:10.1007/s11042-018-6245-5

Cited by 8 publications

(2 citation statements)

References 45 publications

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“…The first type of works (Visual Surveillance of moving object and behavior) is to detect, identify, track specific objects from the sequences of frame image, and to understand and explain the object behaviors. There are a number of publications and researches in the visual surveillance field dealing with implementation of algorithms to perform traditional techniques of image processing such as motion detection [24], [26], [57], [58], object detection [17], [25], [31], [57], [59]- [71], [99], object or event classification [16], [20], [34], [35], [54], [66], [144], [145], [149]- [158], object tracking [2], [7], [15], [32], [35], [56], [70], [98], [99], [134], [136], [139], [159]- [168], behavior and activity recognition [60], [101], [102], [111], [134], [137] and database or system operations [153], [169]- [172]. The aim of the researches is to build intelligent...…”

Section: Research Topic In the Intelligence Video Surveillancementioning

confidence: 99%

A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets

Shidik¹,

Noersasongko²,

Nugraha³

et al. 2019

IEEE Access

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Video surveillance systems obtain a great interest as application-oriented studies that have been growing rapidly in the past decade. The most recent studies attempt to integrate computer vision, image processing, and artificial intelligence capabilities into video surveillance applications. Although there are so many achievements in the acquisition of datasets, methods, and frameworks published, there are not many papers that can provide a comprehensive picture of the current state of video surveillance system research. This paper provides a comprehensive and systematic review on the literature from various video surveillance system studies published from 2010 through 2019. Within a selected study extraction process, 220 journal-based publications were identified and analyzed to illustrate the research trends, datasets, methods, and frameworks used in the field of video surveillance, to provide an in-depth explanation about research trends that many topics raised by researchers as a focus in their researches, to provide references on public datasets that are often used by researchers as a comparison and a means of developing a test method, and to give accounts on the improvement and integration of network infrastructure design to meet the demand for multimedia data. In the end of this paper, several opportunities and challenges related to researches in the video surveillance system are mentioned.INDEX TERMS Artificial intelligence, cloud video surveillance, intelligent video surveillance, video surveillance framework.This study is conducted as follows: the methodology of the study is presented in Section 2. The outcomes and answers to the research questions are then discussed in Section 3. Finally, the study is summarized in the last section.

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Section: Research Topic In the Intelligence Video Surveillancementioning

confidence: 99%

A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets

Shidik¹,

Noersasongko²,

Nugraha³

et al. 2019

IEEE Access

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show abstract

“…A great and increasing number of face recognition-based applications are used in public spaces, thus establishing themselves as a fundamental component of broader and interconnected systems geared toward ensuring safety and security in public spaces. In this context, (smart) cities around the world are becoming key venues where facial recognition applications are used as tools to support the safety and security processes of monitoring and surveilling public spaces [1][2][3][4][5][6][7] . Not surprisingly, the market of products linked to facial recognition technology is expected to grow to $9.6 billion by 2022 8 .Advances in information and communication technology (ICT), and especially the groundbreaking progress in the field of artificial intelligence, including machine learning (ML) and deep learning (DL), translate into new opportunities in the related field of computer vision 9,10 .…”

mentioning

confidence: 99%

Study of image sensors for enhanced face recognition at a distance in the Smart City context

Llauradó,

Pujol,

Tomás

et al. 2023

Sci Rep

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Smart monitoring and surveillance systems have become one of the fundamental areas in the context of security applications in Smart Cities. In particular, video surveillance for Human Activity Recognition (HAR) applied to the recognition of potential offenders and to the detection and prevention of violent acts is a challenging task that is still undergoing. This paper presents a method based on deep learning for face recognition at a distance for security applications. Due to the absence of available datasets on face recognition at a distance, a methodology to generate a reliable dataset that relates the distance of the individuals from the camera, the focal length of the image sensors and the size in pixels of the target face is introduced. To generate the extended dataset, the Georgia Tech Face and Quality Dataset for Distance Faces databases were chosen. Our method is then tested and applied to a set of commercial image sensors for surveillance cameras using this dataset. The system achieves an average accuracy above 99% for several sensors and allows to calculate the maximum distance for a sensor to get the required accuracy in the recognition, which could be crucial in security applications in smart cities.

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OPTrack: A Novel Online People Tracking System

Frikha

Fendri

Hammami

2021

Advances in Intelligent Systems and Computing

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People search based on attributes description provided by an eyewitness for video surveillance applications

Cited by 8 publications

References 45 publications

A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets

A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets

Study of image sensors for enhanced face recognition at a distance in the Smart City context

OPTrack: A Novel Online People Tracking System

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