Distinguishing Individual Red Pandas from Their Faces
This work addresses the costly and inefficient identification methods for red pandas, offering a domain-specific solution for animal conservation and ecology research.
The paper tackles the problem of identifying individual red pandas, an endangered species, by proposing an automatic framework using face images and deep learning models, achieving promising results as evaluated on a self-constructed database.
Individual identification is essential to animal behavior and ecology research and is of significant importance for protecting endangered species. Red pandas, among the world's rarest animals, are currently identified mainly by visual inspection and microelectronic chips, which are costly and inefficient. Motivated by recent advancement in computer-vision-based animal identification, in this paper, we propose an automatic framework for identifying individual red pandas based on their face images. We implement the framework by exploring well-established deep learning models with necessary adaptation for effectively dealing with red panda images. Based on a database of red panda images constructed by ourselves, we evaluate the effectiveness of the proposed automatic individual red panda identification method. The evaluation results show the promising potential of automatically recognizing individual red pandas from their faces. We are going to release our database and model in the public domain to promote the research on automatic animal identification and particularly on the technique for protecting red pandas.