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Abstrak :
Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice.

Abstrak :
ABSTRAK
Sales of video surveillance services, especially those integrated with artificial intelligence based services, should be anticipated by the Indonesian government because it can affect cybersecurity stability. On the one hand, data obtained from the operation of a video surveillance system can be useful for the benefit of national security and or law enforcement. But on the other hand, if the data is controlled and misused by criminals and or terrorists, then cybersecurity risks become large. Institutionally, currently in Indonesia, there are at least 4 government agencies that have duties related to business control of video surveillance services, namely the Ministry of Trade, Ministry of Communication and Information, Republic of Indonesia National Police, and National Cyber and Crypto Agency. However, there is no clarity regarding effective institutional construction to strive so that the interests of cybersecurity stability can run in balance with the interests of increasing the digital economy. By applying a normative legal research methodology based on a conceptual approach, three institutional approaches were found that could be chosen to be included in Indonesia cybersecurity policy. However, the author argues that one institution that has its own authority in supervising the business of video surveillance services is the best solution capable of maintaining Indonesian cybersecurity while protecting the privacy rights of citizens.

Abstrak :
Kemajuan teknologi informasi kini telah dapat membuat kecerdasan buatan (artificial intelligence) yang masuk pada berbagai bidang teknologi, salah satunya yaitu sistem video surveillance. Terintegrasinya sistem video surveillance dengan artificial intelligence membuat sistem dapat melakukan analisis secara otomatis sesuai kebutuhan dari penggunanya yang dapat membantu dalam penegakan hukum, perlindungan keamanan, analisis bisnis, analisis lalu lintas, dan berbagai kegiatan lain dalam implementasinya. Selain memiliki banyak manfaat, dalam penggunaan dan penyelenggaraan sistem video surveillance terdapat dampak negatif pula yang sedang diperdebatkan yaitu isu mengenai privasi, keamanan nasional dan keadilan sosial. Hal ini dapat merugikan tidak hanya individu, namun juga masyarakat keseluruhan bahkan Negara. Belum ada pengaturan yang secara jelas dan eksplisit mengatur mengenai sistem video surveillance di Indonesia, maka dari itu penulis perlu menganalisis secara mendalam peraturan- peraturan di Indonesia dari segi penyelenggara usaha layanan sistem video surveillance yang dikaitkan dengan kewenangan negara mengatur penyelenggaraan usaha, sebab penyelenggaraan usaha juga akan berujung pada penggunaan sistem video surveillance. Penelitian ini bersifat preskriptif dengan pendekatan yuridis-normatif. Di Indonesia pengaturan jasa layanan sistem video surveillance terbagi dalam beberapa klasifikasi usaha yaitu sebagai perdagangan sistem video surveillance, penyelenggara sistem elektronik dan penyelenggara sistem keamanan dengan masing-masing peraturan serta otoritas kewenangan Negara yang menaunginya. Selain itu penulis juga memberikan solusi pengaturan sistem video surveillance yang dirasakan dapat menyeimbangkan kepentingan masing-masing pihak dalam penggunaan dan penyelenggaraan sistem video surveillance yang dianalisis berdasarkan peraturan-peraturan sistem video surveillance pada beberapa Negara. ......The advance of information technology today has integrated the artificial intelligence into several sectors of technology, including the surveillance video system. The integration of video surveillance system with artificial intelligence makes the system able to perform automated analysis according to the needs of its users which can assist in law enforcement, security protection, business analysis, traffic analysis, and various other activities in its implementation. In addition to having many benefits, in the use and organization of video surveillance system there are also negative impacts that are being debated issues of privacy, national security and social justice. It will not only harm the individuals, but also the entire society even the State. There is no clear and explicit regulations on video surveillance system in Indonesia, therefore the writer needs to deeply analyze the regulations in Indonesia in terms of business service provider of video surveillance system which is associated with the state authority to manage the business, because the business will lead to the use of video surveillance systems. This research is prescriptive with juridical-normative approach. In Indonesia the arrangement of video surveillance system services is divided into several business classifications as trading of video surveillance system, electronic system providers and security system providers with their respective rules and authority of the State authority that oversees them. In addition, the authors also provide video surveillance system arrangement solutions that are perceived to balance the interests of each party in the use and organization of video surveillance systems that are analyzed based on video surveillance system regulations in some countries.

Abstrak :
Skripsi ini merupakan pengembangan dari teknologi video surveillance system atau sistem pengawasan video. Video surveillance system yang selama ini diterapkan untuk tujuan deteksi objek menggunakan suatu metode umum yaitu dual background model. Model tersebut bekerja dengan memisahkan latar depan dan latar belakang dari suatu video frame dan memposisikan target deteksi di latar depan sebagai output. Salah satu tujuan dari skripsi ini adalah melakukan pengembangan dari sistem tersebut agar dapat mengklasifikasikan objek yang terdeteksi menjadi abandoned, stolen, dan ghost region. Untuk mencapai tujuan tersebut, digunakan metode pemelajaran mesin Mask R – CNN yang dapat melakukan segmentasi objek berbasis pemaskeran. Selain dari Mask R – CNN, terdapat model pemelajaran mesin lain yang cukup umum digunakan untuk deteksi objek dan segmentasi objek yaitu model YOLACT. Penelitian ini menggunakan video situasi natural di tempat umum seperti stasiun atau jalanan yang akan diproses menggunakan dual background model dan kemudian disegmentasi menggunakan Mask R – CNN atau YOLACT. Hasil penelitian ini diharapkan bisa membuka wawasan tentang penggunaan model pemelajaran mesin dalam aplikasi object detection, sekaligus menganalisis model mana yang paling efektif dan efisien berupa hasil kuantitatif yaitu Frame Rate per Seccond ( FPS ), waktu segmentasi, serta Intersection Over Union ( IOU ). ...... This thesis is an advancement in video surveillance technology. The existing video surveillance system commonly employs a dual background model for object detection. This model functions by separating the foreground and background within a video frame and positions the detected target in the foreground as the output. One of the goals of this thesis is to enhance this system to classify detected objects into abandoned, stolen, and ghost regions. To achieve this, the Mask R-CNN machine learning method is used, which can perform object segmentation based on masking. Apart from Mask R-CNN, another commonly used machine learning model for object detection and segmentation is the YOLACT model. This research utilizes natural situation videos in public places like stations or streets, processed using the dual background model and then segmented using Mask R-CNN or YOLACT. The anticipated outcome of this study is to broaden insights into the use of machine learning models in object detection applications while analyzing which model is most effective and efficient for similar applications.