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Exploring Bias in Primate Face Detection and Recognition

  • Sanchit Sinha
  • Mohit Agarwal
  • Mayank Vatsa
  • Richa SinghEmail author
  • Saket Anand
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11129)

Abstract

Deforestation and loss of habitat have resulted in rapid decline of certain species of primates in forests. On the other hand, uncontrolled growth of a few species of primates in urban areas has led to safety issues and nuisance for the local residents. Hence, identifying individual primates has become the need of the hour - not only for conservation and effective mitigation in the wild but also in zoological parks and wildlife sanctuaries. Primates and human faces share a lot of common features like position and shape of eyes, nose and mouth. It is worth exploring whether the knowledge of human faces and recent methods learned from human face detection and recognition can be extended to primate faces. However, similar challenges relating to bias in human faces will also occur in primates. The quality and orientation of primate images along with different species of primates - ranging from monkeys to gorillas and chimpanzees will contribute to bias in effective detection and recognition. Experimental results on a primate dataset of over 80 identities show the effect of bias in this research problem.

Keywords

Animal biometrics Deep learning Biometrics Bias Face detection Face recognition 

Notes

Acknowledgement

Vatsa, Singh, and Anand are partially supported through Infosys Center for AI at IIIT-Delhi. The authors acknowledge Wildlife Institute of India for sharing the database.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Sanchit Sinha
    • 1
  • Mohit Agarwal
    • 1
  • Mayank Vatsa
    • 1
  • Richa Singh
    • 1
    Email author
  • Saket Anand
    • 1
  1. 1.IIIT-DelhiNew DelhiIndia

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