A Frame-Based Feature Model for Violence Detection from Surveillance Cameras Using ConvLSTM Network

Since the CCTV cameras been introduced in this world, society has started to depend heavily on the usage of this technology for the high security purposes in most of the public and private areas. It is convenient to use these CCTV footages in courts as evidence and has been beneficial many times. But these footages are given priority and checked later when the incident has already taken place and that too after some period of time and not in real-time of happening. The screening of the multiple CCTV footages on a single monitor is done with very less efficiency as the ratio of number of CCTV footages to that of number of surveillance staff is very high. Also, the human unreliable supervision due to many reasons like tiredness from physical or mental effort, worker boredom, or discontinuous observation make the surveillance more inefficient. To address the issue and automatically detect the violent scenes using surveillance cameras and Embedded GPU in real-time we have developed this project for the benefit of our society. As the alert is generated in real-time, the security can take action immediately to prevent any further damage or mishappening in the crowd. Our primary objective is to automatically differentiate between violent activities and non-violent activities through CCTV surveillance cameras and automatically display the security alert on the screen as soon as any violent activity is captured and thus ensuring the safety of our society.

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Violence Detection and Target Finding using Computer Vision

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.e1053.0785s319 ◽

2019 ◽

Vol 8 (5S3) ◽

pp. 235-238

Keyword(s):

Computer Vision ◽

Violent Behavior ◽

Abnormal Behavior ◽

Street Crime ◽

Police Station ◽

Violence Detection ◽

Surveillance Cameras ◽

Automated Technique

Recognizing savagery in recordings through CCTV is basic for requirement and investigation of reconnaissance cameras with the plan of keeping up open wellbeing. Moreover, it will be an incredible device for securing kids and help guardians settles on a superior educated choice about their children. However, this can be a difficult drawback since detecting certain nuances with no human administration isn't entirely technical however also a conceptual problem.So, our idea is to use computer vision to develop an automated technique in detecting the violent behavior/street crime criminals through surveillance cameras installed in cities and towns. When the surveillance cameras detect the abnormal behavior, it captures the scene and generates an alert by sending the captured image to the nearby police station. Further, the CCTV cameras using Cloud trigger the near-by cameras to track the particular target and its location.

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Hybrid Model using Firefly and BBO for Feature Selection in Software Product Line

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200710132013 ◽

2020 ◽

Vol 13 ◽

Author(s):

Hitesh Yadav ◽

Rita Chhikara ◽

Charan Kumari

Keyword(s):

Hybrid Model ◽

High Performance ◽

Software Product Line ◽

Product Line ◽

Feature Model ◽

Software Systems ◽

Feature Sets ◽

Research Article ◽

Software Product ◽

Multiple Variants

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.

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Video as Text/Archive

The Oxford Handbook of Law and Humanities ◽

10.1093/oxfordhb/9780190695620.013.35 ◽

2019 ◽

pp. 778-797

Author(s):

Bennett Capers

Keyword(s):

Supreme Court ◽

Court Case ◽

The Supreme Court ◽

Surveillance Cameras ◽

American Law ◽

Supreme Court Case ◽

History Of ◽

Constitutional Protections

This chapter focuses on a few issues related to video evidence and law, especially with respect to American law. The first issue is the history of the use of video evidence in court. The second issue involves constitutional protections regarding the state’s use of surveillance cameras. The chapter then turns to the Supreme Court case Scott v. Harris to raise concerns about the use of video evidence as not just proof but “truth.” These are of course just a sampling of the issues that the topic of video evidence could raise. The hope is that this chapter will spur further inquiry on the part of the reader.

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Constraints

International Journal of Information System Modeling and Design ◽

10.4018/jismd.2012040102 ◽

2012 ◽

Vol 3 (2) ◽

pp. 33-68 ◽

Cited By ~ 24

Author(s):

Raúl Mazo ◽

Camille Salinesi ◽

Daniel Diaz ◽

Olfa Djebbi ◽

Alberto Lora-Michiels

Keyword(s):

Domain Engineering ◽

Product Line ◽

The Other ◽

Feature Model ◽

Product Configuration ◽

Constraint Program ◽

Engineering Strategy ◽

Application Engineering ◽

The One ◽

Line Engineering

Drawing from an analogy between features based Product Line (PL) models and Constraint Programming (CP), this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. Specifying a PL as a constraint program instead of a feature model carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis (FODA). Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. This paper explores the issues of (a) how to specify a PL model using CP, including in the presence of multi-model representation, (b) how to verify PL specifications, (c) how to specify configuration requirements, and (d) how to support the product configuration activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications.

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A metabolomic endotype of bioenergetic dysfunction predicts mortality in critically ill patients with acute respiratory failure

Scientific Reports ◽

10.1038/s41598-021-89716-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Raymond J. Langley ◽

Marie E. Migaud ◽

Lori Flores ◽

J. Will Thompson ◽

Elizabeth A. Kean ◽

...

Keyword(s):

Respiratory Failure ◽

Acute Respiratory Failure ◽

Patient Outcomes ◽

Medical Intensive Care Unit ◽

Close Association ◽

Treatment Options ◽

Feature Model ◽

High Morbidity ◽

Medical Intensive Care ◽

Poor Outcomes

AbstractAcute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors’ biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition.

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