Smart Prison - Video Analysis for Human Action Detection

Law, Peter Ck; Lau, Wang Yip; Poon, L. C. K.; Chung, Andy Wc; Lai, Ken Wm

doi:10.1109/iecon43393.2020.9255402

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…The transformative impact of smart technology on prison management unfolds across multiple facets, with security enhancement as a foundational element. Real-time monitoring, automated threat detection, and responsive systems collectively bolster the safety and security of prisons [45,46,53,55,56]. Simultaneously, smart technology acts as a catalyst for resource optimization, automating routine tasks, streamlining operations, and empowering prison staff to engage in more intricate aspects of their roles.…”

Section: Implications Of Smart Technology In Prisonsmentioning

confidence: 99%

Unlocking the Potential of Smart Security and Surveillance Technology in Prisons: A Brief Review

Imandeka,

Hidayanto,

Putra

et al. 2024

RIA

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Section: Implications Of Smart Technology In Prisonsmentioning

confidence: 99%

Unlocking the Potential of Smart Security and Surveillance Technology in Prisons: A Brief Review

Imandeka,

Hidayanto,

Putra

et al. 2024

RIA

View full text Add to dashboard Cite

“…Vision detection has good timeliness and can capture behavioural details to enable appropriate intervention methods. For example, Law et al [29] developed a prison aberrant behaviour detection system that can detect aberrant behaviours, such as congregation, falls, self-harm and fights, in inmates through surveillance cameras to improve inmate safety and deal with emergencies. However, collecting labelled data for anomalous events is costly, so the widely preferred method is to train the model on normal training data and test the model on anomalous video data.…”

mentioning

confidence: 99%

Detection of non‐suicidal self‐injury based on spatiotemporal features of indoor activities

Yang

Luo

et al. 2023

IET Biometrics

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Non-suicide self-injury (NSSI) can be dangerous and difficult for guardians or caregivers to detect in time. NSSI refers to when people hurt themselves even though they have no wish to cause critical or long-lasting hurt. To timely identify and effectively prevent NSSI in order to reduce the suicide rates of patients with a potential suicide risk, the detection of NSSI based on the spatiotemporal features of indoor activities is proposed. Firstly, an NSSI behaviour dataset is provided, and it includes four categories that can be used for scientific research on NSSI evaluation. Secondly, an NSSI detection algorithm based on the spatiotemporal features of indoor activities (NssiDetection) is proposed. NssiDetection calculates the human bounding box by using an object detection model and employs a behaviour detection model to extract the temporal and spatial features of NSSI behaviour. Thirdly, the optimal combination schemes of NssiDetection is investigated by checking its performance with different behaviour detection methods and training strategies. Lastly, a case study is performed by implementing an NSSI behaviour detection prototype system. The prototype system has a recognition accuracy of 84.18% for NSSI actions with new backgrounds, persons, or camera angles. K E Y W O R D Sbehavioural sciences computing, computer vision, convolutional neural nets, feature extraction, object detection | INTRODUCTIONNon-suicidal self-injury (NSSI) [1] refers to the direct and repetitive intentional destruction of one's body in the absence of suicidal intent, and its typical behaviours include cutting, severe scratching, burning, biting, climbing and beating. More than 20% of adolescents and over 5% of adults commit self-injury [2,3]. NSSI is one of the emotional outlets for patients with depression, borderline personality disorder and other common mental diseases [4]. Particularly, patients with depression, accounting for 3.8% of the global population [5], are likely to commit NSSI according to the Global Health Data Exchange Platform.Usually, suicidal intent is absent in NSSI, but NSSI behaviours are meant for self-punishment or signal personal pain to the outside world, especially to important persons. NSSI is associated with potential suicide attempts, and this association implies that NSSI behaviours and their related psychology may already be on the same danger trajectory [6]. In addition, evidence shows that over time, raw emotions, such as anxiety, anger and sadness, along with additional feelings of guilt and shame will continue to exist and may even worsen [7].In conclusion, suicide and NSSI are not the same, but NSSI can be dangerous. Guardians or caregivers may have difficulty in determining when a person is hurting himself evenThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Smart Prison - Video Analysis for Human Action Detection

Cited by 2 publications

References 6 publications

Unlocking the Potential of Smart Security and Surveillance Technology in Prisons: A Brief Review

Unlocking the Potential of Smart Security and Surveillance Technology in Prisons: A Brief Review

Detection of non‐suicidal self‐injury based on spatiotemporal features of indoor activities

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