Paper Info
Title
Wildbook: Crowdsourcing, computer vision, and data science for conservation.
Abstract
Photographs, taken by field scientists, tourists, automated cameras, and incidental photographers, are the most abundant source of data on wildlife today. Wildbook is an autonomous computational system that starts from massive collections of images and, by detecting various species of animals and identifying individuals, combined with sophisticated data management, turns them into high resolution information database, enabling scientific inquiry, conservation, and citizen science. We have built Wildbooks for whales (flukebook.org), sharks (whaleshark.org), two species of zebras (Grevyu0027s and plains), and several others. January 2016, Wildbook enabled the first ever full species (the endangered Grevyu0027s zebra) census using photographs taken by ordinary citizens in Kenya. The resulting numbers are now the official species census used by IUCN Red List: this http URL 2016, Wildbook partnered up with WWF to build Wildbook for Sea Turtles, Internet of Turtles (IoT), as well as systems for seals and lynx. Most recently, we have demonstrated that we can now use publicly available social media images to count and track wild animals. In this paper we present and discuss both the impact and challenges that the use of crowdsourced images can have on wildlife conservation.
Year
Venue
Field
2017
arXiv: Computers and Society
Data science,Data mining,Computer science,Crowdsourcing,Wildlife,Citizen science,Artificial intelligence,Census,IUCN Red List,The Internet,Wildlife conservation,Computer vision,Endangered species
DocType
Volume
Citations 
Journal
abs/1710.08880
0
PageRank 
References 
Authors
0.34
7
10
Name
Order
Citations
PageRank
Tanya Y. Berger-Wolf195263.46
Daniel I. Rubenstein2192.81
Charles V. Stewart300.34
Jason A. Holmberg400.34
Jason Parham501.01
Sreejith Menon600.34
Jonathan P. Crall710.68
Jon Van Oast800.34
emre kiciman91446113.79
Lucas Joppa10176.23