You no longer have to turn to Zoboomafoo for your lemur knowledge – a GW researcher found a way to identify the animals faster than ever before.

Rachel Jacobs, a biological anthropologist at GW’s Center for the Advanced Study of Human Paleobiology, coauthored a paper introducing “LemurFaceID.” The computer-assisted recognition system is able to identify individual lemurs in the wild based on their facial characteristics and compile the data for long-term research studies, according to a release.

“Senior author, Stacey Tecot (University of Arizona), and I weren’t particularly satisfied with the common approaches used in lemur research, so we aimed to do something different with red-bellied lemurs, and we sought the expertise of our computer science collaborators,” Jacobs said in the release.

The database will be a non-invasive, cost-effective means of conducting evolutionary studies related to survival, reproduction and population growth, Jacobs said in the release. These studies require long-term life history information on individual animals.

This new tracking method could also help conservation efforts identify endangered species in the wild and tracking trafficked lemurs if they are taken from the wild.

Lemurs were named the world’s most endangered group of mammals in 2012, according to the release.

The database could be applied to other species with similar hair and skin patterns in the future, like red pandas, Jacobs said in the release.