Automated real-time video surveillance summarization framework

Cooharojananone, Nagul; Kasamwattanarote, Siriwat; Lipikorn, Rajalida; Satoh, Shin’ichi

doi:10.1007/s11554-012-0280-7

Cited by 2 publications

(2 citation statements)

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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%

“…Furthermore, it also provides timely warnings to alert security personnels. With the development in sensory technology, surveillance cameras, and sound recording systems, it is possible to provide the intelligent video surveillance system integrated with the realtime monitoring of moving objects within a specific environment [54], [98], [111], [176]- [178].…”

Section: Research Topic In the Intelligence Video Surveillancementioning

confidence: 99%

See 1 more Smart Citation

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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