mlsanityData to 7 Oct 2026

Enhanced Facial Feature Extraction and Recignation Using Optimal Fully Dispersed Haar-like Filters

arXiv 2404.10476 ↗First posted 16 Apr 2024cs.CV cs.NA math.NAcited by 0

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Abstract (arXiv)

Haar-like filters are renowned for their simplicity, speed, and accuracy in various computer vision tasks. This paper proposes a novel algorithm to identify optimal fully dispersed Haar-like filters for enhanced facial feature extraction and recognation. Unlike traditional Haar-like filters, these novel filters allow pixels to move freely within images, enabling more effictive capture of intricate local features...

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 60 references that are in the map. First posted on arXiv 16 Apr 2024.

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6 of 60 references.

References · 6

  1. 2017Age Progression/Regression by Conditional Adversarial Autoencodercited by 426
  2. 2018Deep Facial Expression Recognition: A Surveycited by 269
  3. 2022My Face My Choice: Privacy Enhancing Deepfakes for Social Media Anonymizationcited by 14
  4. 2021Critically examining the Domain Generalizability of Facial Expression Recognition modelscited by 4
  5. 2022A Survey on Computer Vision based Human Analysis in the COVID-19 Eracited by 3
  6. 2019Object recognition and tracking using Haar-like Features Cascade Classifiers: Application to a quad-rotor UAVcited by 2

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