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On Video Based Human Abnormal Activity Detection with Histogram of Oriented Gradients

  • Nadeem Iqbal
  • Malik M. Saad MissenEmail author
  • Nadeem Salamat
  • V. B. Surya Prasath
Chapter

Abstract

Video based activity analysis has applications in surveillance and monitoring, and in recent years various automatic analysis techniques were used to obtain efficient detection of activities. As surveillance cameras are becoming ubiquitous, automatic human activity analysis and abnormal activity recognition in videos are required to handle the big streaming data from these sensors. However, automatic video examination remains challenging due to inter-object occlusions in big crowded scenes, unconstrained motions of people’s activities, and also the quality limitation of acquired videos. Further, to attain robust detection of abnormal actions from surveillance videos there needs to be a separate module of computations that can handle vague, infrequent occurring abnormal activities from noise. In this chapter, we propose a method, that can recognize abnormal activities based on the histogram of oriented gradients approach, that can handle the imprecise visual observations, as well as overcome irregularity of other activity recognition approaches. We develop a static camera human detection with local feature extraction and use Support Vector Machine (SVM) for classification of abnormal activity detection from videos. Experimental results indicate the promise of our approach in with good precision with less false positive activity frames.

Keywords

Abnormal activity Human detection Video analysis Image analysis Anomaly detection Variance Hog 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nadeem Iqbal
    • 1
  • Malik M. Saad Missen
    • 1
    Email author
  • Nadeem Salamat
    • 2
  • V. B. Surya Prasath
    • 3
    • 4
  1. 1.Department of Computer Science and ITThe Islamia University of BahawalpurBahawalpurPakistan
  2. 2.Department of MathematicsKhawaja Fareed University of Engineering and Information Technology (KFUIT)Rahim Yar KhanPakistan
  3. 3.Division of Biomedical InformaticsCincinnati Children’s Hospital Medical CenterCincinnatiUSA
  4. 4.Department of Pediatrics, College of MedicineUniversity of CincinnatiCincinnatiUSA

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