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Facial Key-Point Detection and Real-Time Filtering Using Convolutional Neural Network

Author

Listed:
  • Abhishek G C
  • Pramukh B V
  • Pranav T V
  • Shravan S Vasista
  • B S Prathibha

Abstract

In this paper, an effort is made to combine the knowledge of computer vision techniques and deep learning to build and end-to-end facial keypoint recognition system. Facial keypoints include points around the eyes, nose, and mouth on any face and are used in many applications, from facial tracking to emotion recognition. The partially complete module should be able to take in any image containing faces and identify the location of each face and their facial keypoints. The proposed facial recognition system uses few of the many computer vision algorithms built into the OpenCV library and are implemented at the basic level. This expansive computer vision library is open source and is still growing. The proposed system does real time filtering and facial key point detection. This implementation uses a Convolutional Neural Network to train the system at each step, visualize the loss and learn in the next detection.

Suggested Citation

  • Abhishek G C & Pramukh B V & Pranav T V & Shravan S Vasista & B S Prathibha, 2018. "Facial Key-Point Detection and Real-Time Filtering Using Convolutional Neural Network," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 4(6), pages 228-232, May.
    • Handle: RePEc:jbh:ijsrcs:v4:y2018:i6:id:hcseit184644
    Note: Article URL: https://ijsrcseit.com/CSEIT184644
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