Real time Face Detection

  • Avinash Mishra
  • Harish Chandrasekaran
  • Bhavesh Dhamecha
  • Radhika Bhise
Keywords: Face detection, AdaBoost Algorithm, Cascade Classifier, Haar cascade classifier, Local binary pattern classifier, Histogram of oriented gradients, Haar-Like features, Viola-Jones.

Abstract

Face detection puts forth a challenging problem in the field of Computer Vision. Detecting faces in real time have many applications especially in the safety and security domain. The primary aim of Face detection algorithms is to detect faces in an image or in a video stream successfully so that they could be further used for applications such as Face recognition. Object detection systems developed traditionally have had a lot of success in detecting objects such as humans, cars, buildings etc. but real time face detection presents a new challenge. In this paper, we provide efficient and robust face detection algorithms which adapt to real-world situations like the face being in poor light conditions, multiple faces in a window, pose, different orientations, varied expressions, to detect faces with maximum accuracy.

References

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Published
2020-03-26
How to Cite
Mishra, A., Chandrasekaran, H., Dhamecha, B., & Bhise, R. (2020). Real time Face Detection. Asian Journal For Convergence In Technology (AJCT), 5(3), 17-19. Retrieved from http://www.asianssr.org/index.php/ajct/article/view/906