Direction estimation of crowd flow in surveillance videos

Anees, V Muhammed; Kumar, G. Santhosh

doi:10.1109/tenconspring.2017.8070040

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…The detected spot area was limited to

pixels, droplets were screened and bright spots were suppressed by setting the roundness and convexity of spots. The roundness of spots is shown in Equation (2), and the convexity is shown in Equation (3) [ 35 , 36 ]. The value range of the two is 0–1.…”

Section: Methodsmentioning

confidence: 99%

Image Segmentation and Quantification of Droplet dPCR Based on Thermal Bubble Printing Technology

Zhu

Zhang

Wei

et al. 2022

Sensors

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Thermal inkjet printing can generate more than 300,000 droplets of picoliter scale within one second stably, and the image analysis workflow is used to quantify the positive and negative values of the droplets. In this paper, the SimpleBlobDetector detection algorithm is used to identify and localize droplets with a volume of 24 pL in bright field images and suppress bright spots and scratches when performing droplet location identification. The polynomial surface fitting of the pixel grayscale value of the fluorescence channel image can effectively compensate and correct the image vignetting caused by the optical path, and the compensated fluorescence image can accurately classify positive and negative droplets by the k-means clustering algorithm. 20 µL of the sample solution in the result reading chip can produce more than 100,000 effective droplets. The effective droplet identification correct rate of 20 images of random statistical samples can reach more than 99% and the classification accuracy of positive and negative droplets can reach more than 98% on average. This paper overcomes the problem of effectively classifying positive and negative droplets caused by the poor image quality of photographed picolitre ddPCR droplets caused by optical hardware limitations.

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“…The detected spot area was limited to

Section: Methodsmentioning

confidence: 99%

Image Segmentation and Quantification of Droplet dPCR Based on Thermal Bubble Printing Technology

Zhu

Zhang

Wei

et al. 2022

Sensors

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“…This makes the movements of such groups represent another challenge to crowd management. Anees et al [4] developed an approach to determine the direction of the global movement of the crowd. The dense areas were identified using key-point descriptors, which ultimately contributed to finding the flow direction.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Among the most effective measures to limit the spread of coronavirus are face masks and the implementation of social distancing. Crowd density, the average number of people in a scene, could be exploited to determine the crowd's direction [4]. Crowd events such as local dispersion, running, crowd splitting, evacuation, and crowd formation must be identified quickly [5].…”

Section: Introductionmentioning

confidence: 99%

Sparse Crowd Flow Analysis of Tawaaf of Kaaba During the COVID-19 Pandemic

Durr-e-Nayab¹,

Qamar²,

Khan³

et al. 2022

Computers, Materials &Amp; Continua

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The advent of the COVID-19 pandemic has adversely affected the entire world and has put forth high demand for techniques that remotely manage crowd-related tasks. Video surveillance and crowd management using video analysis techniques have significantly impacted today's research, and numerous applications have been developed in this domain. This research proposed an anomaly detection technique applied to Umrah videos in Kaaba during the COVID-19 pandemic through sparse crowd analysis. Managing the Kaaba rituals is crucial since the crowd gathers from around the world and requires proper analysis during these days of the pandemic. The Umrah videos are analyzed, and a system is devised that can track and monitor the crowd flow in Kaaba. The crowd in these videos is sparse due to the pandemic, and we have developed a technique to track the maximum crowd flow and detect any object (person) moving in the direction unlikely of the major flow. We have detected abnormal movement by creating the histograms for the vertical and horizontal flows and applying thresholds to identify the non-majority flow. Our algorithm aims to analyze the crowd through video surveillance and timely detect any abnormal activity to maintain a smooth crowd flow in Kaaba during the pandemic.

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“…These capabilities have been studied from different perspectives leading to a wide range of results including threats and individuals detection (Chackravarthy, Schmitt, & Yang, 2018) (Bellini, Cenni, Nesi, & Paoli, 2017), screening and tracking (Brust, y otros, 2017) (Anees & Kumar, 2017), recognition-based authentication (Balla & Jadhao, 2018) (Boukerche, Siddiqui, & Mammeri, 2017) or the improvement of legacy systems deployed throughout the city endowing them with intelligence (Zingoni, Diani, & Corsini, 2017) (Zhou, Saha, & Rangarajan, 2015). However, due to our particular approach, we must emphasise that there are hardly any studies (Dbouk, Mcheick, & Sbeity, 2014) (Bonatsos, Middleton, Melas, & Sabeur, 2013) that propose a comprehensive DSS involving at the same time emergency management, real-time decision support and forecasting of threats evolution and impact of most common terrorist attacks.…”

Section: Introductionmentioning

confidence: 99%

Decision-Support System for Safety and Security Assessment and Management in Smart Cities

González‐Villa

Cuesta²,

Spagnolo³

et al. 2022

Lecture Notes in Computer Science

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Counter-terrorism and its preventive and response actions are crucial factors in security planning and protection of mass events, soft targets and critical infrastructures in urban environments. This paper presents a comprehensive Decision Support System developed under the umbrella of the S4AllCitites project, that can be integrated with legacy systems deployed in the Smart Cities. The system includes urban pedestrian and vehicular evacuation, considering ad-hoc predictive models of the evolution of incendiary and mass shooting attacks in conjunction with a probabilistic model for threat assessment in case of improvised explosive devices. The main objective of the system is to provide decision support to public or private security operators in the planning and real time phases in the prevention or intervention against a possible attack, providing information on evacuation strategies, the probability or expected impact of terrorist threats and the state of the traffic network in normal or unusual conditions allowing the emergency to be managed throughout its evolution.

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Direction estimation of crowd flow in surveillance videos

Cited by 7 publications

References 13 publications

Image Segmentation and Quantification of Droplet dPCR Based on Thermal Bubble Printing Technology

Image Segmentation and Quantification of Droplet dPCR Based on Thermal Bubble Printing Technology

Sparse Crowd Flow Analysis of Tawaaf of Kaaba During the COVID-19 Pandemic

Decision-Support System for Safety and Security Assessment and Management in Smart Cities

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