Abstract:
Deforestation and loss of habitat have resulted in a rapid decline of certain species of primates in forests. On the other hand, the uncontrolled growth of a few species of primates in urban areas has led to safety issues and a 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. Along with bias analysis, we also propose a novel recognition framework for the recognition of primates using transform learning. The results of the following project were published in the Proceedings of European Conference on Computer Vision Workshop on Bias Estimation in Face Analytics, 2018 and are submitted to the International Conference on Image Processing, 2019.