Automatic Identification of Individual Primates with Deep Learning Techniques

Songtao Guo; Pengfei Xu; Qiguang Miao; Guofan Shao; Colin A Chapman; Xiaojiang Chen; Gang He; Dingyi Fang; He Zhang; Yewen Sun; Zhihui Shi; Baoguo Li

doi:10.1016/j.isci.2020.101412

Automatic Identification of Individual Primates with Deep Learning Techniques

iScience. 2020 Aug 21;23(8):101412. doi: 10.1016/j.isci.2020.101412. Epub 2020 Jul 25.

Authors

Songtao Guo¹, Pengfei Xu², Qiguang Miao³, Guofan Shao⁴, Colin A Chapman⁵, Xiaojiang Chen², Gang He⁶, Dingyi Fang², He Zhang⁶, Yewen Sun⁶, Zhihui Shi⁶, Baoguo Li⁷

Affiliations

¹ Shaanxi Key Laboratory for Animal Conservation, School of Life Sciences, Northwest University, Xi'an 710069, China. Electronic address: songtaoguo@nwu.edu.cn.
² School of Information Sciences and Technology, Northwest University, Xi'an 710127, China; Shaanxi International Joint Research Centre for the Battery-free Internet of Things, Xi'an, China; Institute of Internet of Things, Northwest University, Xi'an, China.
³ School of Computer Science and Technology, Xidian University, Xi'an 710071, China; Xi'an Key Laboratory of Big Data and Intelligent Vision, Xi'an 710071, China.
⁴ Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47907, USA.
⁵ Shaanxi Key Laboratory for Animal Conservation, School of Life Sciences, Northwest University, Xi'an 710069, China; Department of Anthropology, Center for the Advanced Study of Human Paleobiology, George Washington University, Washington, DC 20037, USA; School of Life Sciences, University of KwaZulu-Natal, Scottsville, Pietermaritzburg 3209, South Africa.
⁶ Shaanxi Key Laboratory for Animal Conservation, School of Life Sciences, Northwest University, Xi'an 710069, China.
⁷ Shaanxi Key Laboratory for Animal Conservation, School of Life Sciences, Northwest University, Xi'an 710069, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China.

Abstract

The difficulty of obtaining reliable individual identification of animals has limited researcher's ability to obtain quantitative data to address important ecological, behavioral, and conservation questions. Traditional marking methods placed animals at undue risk. Machine learning approaches for identifying species through analysis of animal images has been proved to be successful. But for many questions, there needs a tool to identify not only species but also individuals. Here, we introduce a system developed specifically for automated face detection and individual identification with deep learning methods using both videos and still-framed images that can be reliably used for multiple species. The system was trained and tested with a dataset containing 102,399 images of 1,040 individuals across 41 primate species whose individual identity was known and 6,562 images of 91 individuals across four carnivore species. For primates, the system correctly identified individuals 94.1% of the time and could process 31 facial images per second.

Keywords: Artificial Intelligence; Ethology; Zoology.