COLLABORATIVE RESEARCH: ABI Innovation: Computational and Informatics Tools for Supporting Collaborative Wildlife Monitoring and Research

University Of Missouri-Columbia, Columbia MO

Investigators

Abstract

The University of Missouri and the University of Illinois at Urbana-Champaign are awarded collaborative grants to develop advanced computational and informatics tools that will support wildlife data collection, analysis, and management at large scales. Project objectives include investigation of 1) advanced computer vision methods for detecting and tracking animals in dynamic and cluttered environments; 2) adaptive classification, machine learning, and information fusion methods for recognizing animal species and individual ID; and 3) data summarization and database management schemes to support collaborative wildlife research. The performance of these computational and informatics tools will be evaluated using existing camera trap datasets and field studies in terms of their potential to support collaborative wildlife research. This project will broadly advance the state-of-the-art in computer vision, wildlife monitoring, ecology, and conservation research. It will provide new methods and tools for automated processing and mining of massive wildlife monitoring data at large scales. This will allow individual or coordinated networks of wildlife researchers to analyze and manage camera-trap data with minimum effort and compare and share data between research groups across different geographical regions. Collaborative wildlife monitoring and tracking at large geographical and time scales will help us understand the complex dynamics of wildlife systems, evaluate the impact of human actions and environmental changes on wildlife species, and answer many important wildlife, ecological, and conservation research questions. The database will be hosted by Smithsonian. This will provide exciting interdisciplinary opportunities for mentoring graduate students and involving K-12 and undergraduate students into professionally guided research. Software and results of this project will be available from the website http://videonet.ece.missouri.edu.