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Static Summarization Using Pearson’s Coefficient and Transfer Learning for Anomaly Detection for Surveillance Videos

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Information Management and Big Data (SIMBig 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1410))

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Abstract

Data storage has been a problem as technology advances, there are more devices capable of capturing images, sounds, videos, etc. On the security side, many people choose to use security cameras that are available 24 h a day to capture anomalous events and maintain the security of the area, however, storing all captured videos generates high costs, as well as the prolonged analysis that this type of videos implies. For this reason, we propose a method that allows selecting only the important events captured by a video surveillance camera and then classifying them among the types of most constant criminal acts in Peru.

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Notes

  1. 1.

    Seagate - https://bit.ly/31wPnfn.

  2. 2.

    Magazine “Lima como Vamos” - https://bit.ly/394n6i3.

  3. 3.

    INEI - https://www.inei.gob.pe/.

  4. 4.

    https://www.crcv.ucf.edu/projects/real-world/.

  5. 5.

    “Lima como Vamos” - https://bit.ly/2BAdj78.

  6. 6.

    INEI - https://bit.ly/39F7FgD.

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Author information

Authors and Affiliations

  1. University of Applied Sciences (UPC), Lima, Peru

    Steve Willian Chancolla-Neira, César Ernesto Salinas-Lozano & Willy Ugarte

Authors
  1. Steve Willian Chancolla-Neira
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  2. César Ernesto Salinas-Lozano
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  3. Willy Ugarte
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Corresponding author

Correspondence to Willy Ugarte .

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Editors and Affiliations

  1. Stanford University, Stanford, CA, USA

    Juan Antonio Lossio-Ventura

  2. Visibilia, São Paulo, Brazil

    Jorge Carlos Valverde-Rebaza

  3. University of Valencia, Valencia, Spain

    Eduardo Díaz

  4. Universidad del Pacífico, Lima, Peru

    Hugo Alatrista-Salas

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Chancolla-Neira, S.W., Salinas-Lozano, C.E., Ugarte, W. (2021). Static Summarization Using Pearson’s Coefficient and Transfer Learning for Anomaly Detection for Surveillance Videos. In: Lossio-Ventura, J.A., Valverde-Rebaza, J.C., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2020. Communications in Computer and Information Science, vol 1410. Springer, Cham. https://doi.org/10.1007/978-3-030-76228-5_20

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  • DOI: https://doi.org/10.1007/978-3-030-76228-5_20

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