Mining anomalous events against frequent sequences in surveillance videos from commercial environments

Anwar, Fahad; Petrounias, Ilias; Morris, Tim; Kodogiannis, Vassilis

doi:10.1016/j.eswa.2011.09.134

Cited by 16 publications

(9 citation statements)

References 36 publications

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“…The advantage of rule based system is that easy to recognize new events by modifying some rules. The main steps involved in a recognition system are Mining anomalous events against frequent sequences in surveillance videos from commercial environments [89] focus on abnormal events linked with frequent chain of events. The main result in identifying such events is early deployment of resources in particular areas.…”

Section: Methods Identified/reviewed Other Than Deep Learningmentioning

confidence: 99%

Intelligent video surveillance: a review through deep learning techniques for crowd analysis

2019

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Section: Methods Identified/reviewed Other Than Deep Learningmentioning

confidence: 99%

Intelligent video surveillance: a review through deep learning techniques for crowd analysis

2019

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“…The authors in (Anwar, Petrounias, Morris, and Kodogiannis, 2012) have developed an anomaly detection method to analyze anomalous events. However, the proposed method works at microscopic level.…”

Section: Computer Vision-based Methodsmentioning

confidence: 99%

Estimation of linear motion in dense crowd videos using Langevin model

Behera

Dogra

Bandyopadhyay

et al. 2020

Expert Systems with Applications

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Crowd gatherings at social and cultural events are increasing in leaps and bounds with the increase in population. Surveillance through computer vision and expert decision making systems can help to understand the crowd phenomena at large gatherings. Understanding crowd phenomena can be helpful in early identification of unwanted incidents and their prevention. Motion flow is one of the important crowd phenomena that can be instrumental in describing the crowd behavior. Flows can be useful in understanding instabilities in the crowd. However, extracting motion flows is a challenging task due to randomness in crowd movement and limitations of the sensing device. Moreover, low-level features as compared to existing popular crowd segmentation methods. The evaluation of the proposed model has been carried out on publicly available datasets as well as using our dataset. It has been observed that the proposed method is able to estimate and segment the linear flows in the dense crowd with better accuracy as compared to state-of-the-art techniques with substantial decrease in the computational overhead.

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“…BI is also characterised as a non-financial measurement tool, which supports a firm by using multi-dimensional and unstructured data (Gao andXu, 2009, Chaudhuri et al, 2011). This data could include pictures (Anwar et al, 2012), online product reviews (Chung and Tseng, 2012), blog entries (Chau and Xu, 2012), search portals (Roussinov and Chau, 2008), customer behaviour (Hsieh, 2011), market survey reports, project status reports, meeting records, customer complaints, e-mails, patent application sheets and competitor advertisements, all recorded in documents (Tseng and Chou, 2006). BI's characteristics for a financial measurement system include transaction data, (Ramakrishnan et al, 2012), fraudulent financial data, authentic data, bank status data, or interbank payment data (Hu et al, 2012), which provides the players involved, such as executives, managers, business analysts and others in a firm (Popovič et al, 2014) with adequate information for decision-making.…”

Section: Micro Level Of Bimentioning

confidence: 99%

Technology in its Context

Fischer

2017

IJBIDM

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The purpose of the literature review is to identify characteristics, concepts, and theories of business intelligence (BI). The status quo of BI is based on the literature review, which covers 86 journal articles from the three areas of accounting, strategy, and information systems between 2006 and 2014. The review combines two established frameworks to illustrate new insights regarding the macro and micro levels of BI. The complementary combination of both levels produces a new lens that shows the conceptualisation and characteristics of BI in a holistic view. The result of the study shows that BI is used as a monolithic concept and static tool with technical control mechanisms. Another result implies that BI is in a phase of maturity, in which it fulfils an organisational purpose without considering its social context or ecosystem in which it occurs. The literature review contributes to the characterisation and theorisation of BI and shows that a company depend on both characteristics and the purpose for which BI is used.

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Mining anomalous events against frequent sequences in surveillance videos from commercial environments

Cited by 16 publications

References 36 publications

Intelligent video surveillance: a review through deep learning techniques for crowd analysis

Intelligent video surveillance: a review through deep learning techniques for crowd analysis

Estimation of linear motion in dense crowd videos using Langevin model

Technology in its Context

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