Efficient Motion Encoding Technique for Activity Analysis at ATM Premises

  • Prateek BajajEmail author
  • Monika Pandey
  • Vikas Tripathi
  • Vishal Sanserwal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 713)


Automated teller machines (ATMs) have become the predominant banking channel for the majority of customer transactions. However, despite the multitudinous advantages of ATM, it lacks in providing security measures against ATM frauds. Video surveillance is one of the prominent measures against ATM frauds. In this paper, we present an approach that can be used for activity recognition in small premises such as ATM rooms by encoding the motion in images. We have used gradient-based descriptor (HOG) to extract features from image sequences. The features obtained are classified using random forest classifier. Our employed method is successful in determining abnormal and normal human activities both in case of single and multiple personnel with an average accuracy of 97%.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Prateek Bajaj
    • 1
    Email author
  • Monika Pandey
    • 1
  • Vikas Tripathi
    • 1
  • Vishal Sanserwal
    • 1
  1. 1.Department of Computer Science and EngineeringGraphic Era UniversityDehradunIndia

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