Visual Informatics Tools for Supporting Large-Scale Collaborative Wildlife Monitoring with Citizen Scientists

Zhihai He, Roland Kays, Zhi Zhang, Guanghan Ning, Chen Huang, Tony X. Han, Josh Millspaugh, Tavis Forrester, William McShea

Research output: Contribution to journalArticlepeer-review

Abstract

Collaborative wildlife monitoring and tracking at large 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 ecological and evolutionary research questions. To support collaborative wildlife monitoring and research, we need to develop integrated camera-sensor networking systems, deploy them at large scales, and develop advanced computational and informatics tools to analyze and manage the massive wildlife monitoring data. In this paper, we will cover various aspects of the design of such systems, including (1) long-lived integrated camera-sensor system design, (2) image processing and computer vision algorithms for animal detection, segmentation, tracking, species classification, and biometric feature extraction, (3) cloud-based data management, (4) crowd-sourcing based image annotation with citizen scientists, and (5) applications to wildlife and ecological research.

Original languageEnglish
Article number7404334
Pages (from-to)73-86
Number of pages14
JournalIEEE Circuits and Systems Magazine
Volume16
Issue number1
DOIs
StatePublished - Jan 1 2016

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