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Study on Different Region-Based Object Detection Models Applied to Live Video Stream and Images Using Deep Learning

Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB,volume 30)

Abstract

There is a plenty of very interesting problems in the field of computer vision, from the very basic image classification problem to 3d pose estimation problem. One among the many interesting problems is object detection, which is the computer capability to accurately identify the multiple objects present in the scene (image or video) with the bounding boxes around them and the appropriate labels indicating their class along with the confidence score indicating the degree of closeness with the class. In this work, we have discussed in detail different types of region-based object detection models applied on both live video stream and images.

Keywords

  • Object detection
  • Deep learning
  • Convolutional neural network
  • Computer vision
  • Single-shot detector
  • You look only once
  • Selective search
  • Region of interest
  • Region proposal network

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Acknowledgements

We are thankful to NMAM Institute of Technology and Engineering Nitte, for allowing us to take the images required for performing the experiment.

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Correspondence to Pawan S. Jogi .

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Shetty, J., Jogi, P.S. (2019). Study on Different Region-Based Object Detection Models Applied to Live Video Stream and Images Using Deep Learning. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_6

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  • DOI: https://doi.org/10.1007/978-3-030-00665-5_6

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-00665-5

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