Computer Vision: A Review of Detecting Objects in Videos – Challenges and Techniques

Authors

  • Mohammad Ali A. Hammoudeh Department of Information Technology, College of Computer, Qassim University, Buraydah 51941, Saudi Arabia
  • Mohammad Alsaykhan Department of Information Technology, College of Computer, Qassim University, Buraydah 51941, Saudi Arabia
  • Ryan Alsalameh Department of Information Technology, College of Computer, Qassim University, Buraydah 51941, Saudi Arabia
  • Nahs Althwaibi Department of Information Technology, College of Computer, Qassim University, Buraydah 51941, Saudi Arabia

DOI:

https://doi.org/10.3991/ijoe.v18i01.27577

Keywords:

Computer Vision, Traffic Safety Applications, Object Detection, AI models, Video Analysis, Convolutional Neural Network, Tensor-Flow, Lanes Viola-tion Tracking

Abstract


Traffic safety aims to change the attitude of citizens towards careless traffic on the roads, making this the first step towards changing behavior. Also, teach the rules of safe pedestrian behavior and minimize the risks of road accidents. So many regulations have been set to avoid road accidents and traffic jams, which is the study scope of this paper using IT technology. With the expanding interests in Computer vision use cases such as vehicles self-driving, face recognition, intelligent transportation frameworks and so on individuals are hoping to assemble custom AI models to recognize and distinguish specific objects. Object detection is part of a computer's vision where objects that can be observed externally and are found in videos can be identified and tracked by computers. Therefore, object tracking is an important part of video analysis. There are many proposed methods such as Tracking, Learning, Detection, Mean shift and MIL. In this paper, the computer vision state in object detecting domain along with its challenges are discussed, also we address some requirements and techniques to overcome these challenges. Finally, TensorFlow technology is presented as a recommended solution to support Lane’s violation.
Covr iJOE Vol. 18 No. 01 (2022)

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Published

2022-01-26

How to Cite

Hammoudeh, M. A. A., Alsaykhan, M., Alsalameh, R., & Althwaibi, N. (2022). Computer Vision: A Review of Detecting Objects in Videos – Challenges and Techniques. International Journal of Online and Biomedical Engineering (iJOE), 18(01), pp. 15–27. https://doi.org/10.3991/ijoe.v18i01.27577

Issue

Vol. 18 No. 01 (2022)

Section

Papers

License

Copyright (c) 2021 Mohammad Ali A. Hammoudeh, Mohammad Alsaykhan, Ryan Alsalameh, Nahs Althwaibi

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