Hierarchical spatial object detection for ATM vandalism surveillance

Jun Yeop Lee, Chul Jin Cho, David K. Han, Hanseok Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a multi-modal classification is proposed for recognizing vandalism against Automatic Teller Machines (ATMs). The visual and textual information base model is developed here to identify external threats on ATMs. The model discriminates threatening behaviors from those that are benign in the image. It provides a level of confidence in the threat recognition by visual object classification coupled with word vector distance measure. To achieve our goal, real-time object detection based on a Region Convolutional Neural Network (R-CNN) first detects objects in the scene and word embedding technique allows to measure distance between the detected object label with predefined tools assumed to be used for vandalizing ATMs. Similarity measure from word embedding not only determines whether the scene may lead to any nefarious activities, but also would provide the level of confidence in occurrence of such incidents. From the experimental evaluation, it is shown that the method is effective and delivers a quantitative measure on decisions it makes.

Original languageEnglish
Title of host publicationProceedings of AVSS 2018 - 2018 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538692943
DOIs
Publication statusPublished - 2019 Feb 11
Event15th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2018 - Auckland, New Zealand
Duration: 2018 Nov 272018 Nov 30

Publication series

NameProceedings of AVSS 2018 - 2018 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance

Conference

Conference15th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2018
CountryNew Zealand
CityAuckland
Period18/11/2718/11/30

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Media Technology

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  • Cite this

    Lee, J. Y., Cho, C. J., Han, D. K., & Ko, H. (2019). Hierarchical spatial object detection for ATM vandalism surveillance. In Proceedings of AVSS 2018 - 2018 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance [8639154] (Proceedings of AVSS 2018 - 2018 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AVSS.2018.8639154