People tracking in multi-camera systems: a review

Iguernaissi, Rabah; Merad, Djamal; Aziz, Kheir-Eddine; Drap, Pierre

doi:10.1007/s11042-018-6638-5

Cited by 33 publications

(16 citation statements)

References 74 publications

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“…Saat ini, manfaat dari pelacakan orang dalam pengawasan sering kita jumpai di berbagai tempat, seperti perkotaan, perkantoran, bandara, dll. Hal tersebut dipakai untuk kebutuhan sistem keamaan dan pengenalan aktivitas sosial (Iguernaissi, Merad , Aziz, & Drap, 2019). Penggunaan kamera tunggal tidak akan bekerja dengan maksimal apabila memiliki keterbatasan field of view.…”

Section: Pendahuluanunclassified

Skema Handover pada Multi-kamera dengan Logika Fuzzy untuk Sistem Pemantauan Orang

2021

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ABSTRAKAdanya berbagai peristiwa yang membahayakan di tempat keramaian menyebabkan diperlukannya sebuah sistem pemantauan aktifitas manusia di sekitarnya untuk pengawasan keamanan. Sistem multi-kamera sangat cocok digunakan untuk pemantauan target pada lingkungan area yang luas. Disaat target meninggalkan jangkauan area kamera menuju lainnya, proses pemantauan target harus tetap bekerja dan diserahkan ke kamera lainnya. Protokol serah terima target dapat berjalan jika terdapat komunikasi antar kamera yang tersedia. Penelitian ini menyajikan skema handover pada sistem multi-kamera dengan menerapkan pengambilan keputusan handover berbasis logika fuzzy. Dengan begitu, target akan selalu ditangani oleh kamera meskipun target bergerak menjauhinya. Berdasarkan hasil simulasi, skema handover ini mampu mereduksi total number of handover sebesar 20% dibandingkan dengan metode AHCS (Active Handover Control Scheme). Selain itu, handover delay pada metode usulan memperoleh waktu 123.72μs dan masih lebih lama dari AHCS.Kata kunci: handover, multi-kamera, pemantauan orang, fuzzy logic ABSTRACTThe existence of various dangerous events in a crowded place causes the need of surveillance system to monitor the human activity continuously in a certain area. Multi-camera systems are used to monitor targets in large areas. When the target leaves the camera’s range for another, the target monitoring process should continue to work and be left to other cameras. The target handover protocol may work if there is communication between the available cameras. This document presents a handover scheme in a multi-camera system by applying a fuzzy logic handover decision. Thus, the target will always be processed by the camera, even if the target is moving away from it. Based on the simulation results, this handover scheme is able to reduce the total number of handovers by 20% compared to the AHCS (Active Handover Control Scheme) method. In addition, the handover delay in the proposed method obtains 123.72 μs and is still longer than the AHCS.Keywords: handover, multi-camera, human monitoring, fuzzy logic

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Section: Pendahuluanunclassified

Skema Handover pada Multi-kamera dengan Logika Fuzzy untuk Sistem Pemantauan Orang

2021

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“…Most of the algorithms used in multi-camera tracking are adopted from single-camera tracking with a modification that caters to multiple cameras. There are many approaches adopted from literature towards classifying a multi-camera tracking system, some are based on cameras' FOV [17], motion detection, and camera architecture [16]. Figure 8 depict the multi-camera tracking classification.…”

Section: Multi-camera System Algorithmsmentioning

confidence: 99%

“…The figure shows that the number of publications related to the multi-camera system is in the increasing trend, which indicates that research on the multi-camera system is still very popular in the present day. Even though several surveys concerning multi-camera systems have been published, virtually all of them focused on a selected aspect of the multi-camera system and particular areas of its applications (e.g., tracking or surveillance) [11] [12] [13] [14] [15] [16] [17]. These surveys, of course, do not cover the wide spectrum of multi-camera system studies.…”

Section: Introductionmentioning

confidence: 99%

Literature Survey on Multi-Camera System and Its Application

2020

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A multi-camera system combines features from different cameras to exploit a scene of an event to increase the output image quality. The combination of two or more cameras requires prior settings in terms of calibration and architecture. Therefore, this paper surveys the available literature in terms of multi-camera systems' physical arrangements, calibrations, algorithms, and their advantages and disadvantages. We also survey the recent developments and advancements in four areas of multi-camera system applications, which are surveillance, sports, education, and mobile phones. In the surveillance system, the combination of multiple heterogeneous cameras and the discovery of Pan-Tilt-Zoom (PTZ) and smart cameras have brought tremendous achievements in the area of multi-camera control and coordination. Different approaches have been proposed to facilitate effective collaboration and monitoring among the camera network. Furthermore, the application of multi-cameras in sports has made the games more interesting in the aspect of analyses and transparency. The application of the multi-camera system in education has taken education beyond the four walls of the class. The method of teaching, student attendance enrollment, determination of students' attention, teacher and student assessment can now be determined with ease, and all forms of proxy and manipulation in education can be reduced by using a multi-camera system. Besides, the number of cameras featuring on smartphones is gaining noticeable recognition. However, most of these cameras serve different purposes, from zooming, telephoto, and wider Field of View (FOV). Therefore, future smartphones should be expecting more cameras or the development would be in a different direction.

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“…Pedestrian attributes, such as gender, age, and clothing, are conducive to person re-identification [11]. Generally, based on the person re-identification result and combined with geographical location and regional distribution, the trail of the target person can be mapped, which is multi-target multi-camera (MTMC) tracking technology [12]. Fig.…”

Section: A Development Coursementioning

confidence: 99%

A Comprehensive Overview of Person Re-Identification Approaches

Wang

Zhao

et al. 2020

IEEE Access

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Person re-identification, identifying and tracking pedestrians in cross-domain monitoring systems, is an important technology in the computer vision field and of real significance for the construction of smart cities. With the development of deep learning techniques, especially convolutional neural networks, this technology has received more extensive attention and improvement in recent years and a large number of noteworthy achievements have emerged. This paper provides a comprehensive overview of person re-identification approaches to assist researchers in quickly understand this field with preference as well as to provide a more structured framework. By reviewing more than 300 re-identification related papers, the focus of these studies is summarized as information extraction, metric learning, post-processing, efficiency improvement, labeling cost reduction, and data type expansion. This classification is then organized based on different technologies, and on this basis, the pros and cons of each technology are analyzed. Moreover, this overview summarizes the difficulties and challenges of re-identification and discusses the possible research directions for reference. INDEX TERMSComputer vision, convolutional neural networks, distance learning, feature extraction, person re-identification.

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People tracking in multi-camera systems: a review

Cited by 33 publications

References 74 publications

Skema Handover pada Multi-kamera dengan Logika Fuzzy untuk Sistem Pemantauan Orang

Skema Handover pada Multi-kamera dengan Logika Fuzzy untuk Sistem Pemantauan Orang

Literature Survey on Multi-Camera System and Its Application

A Comprehensive Overview of Person Re-Identification Approaches

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