TY - JOUR
T1 - Visual Informatics Tools for Supporting Large-Scale Collaborative Wildlife Monitoring with Citizen Scientists
AU - He, Zhihai
AU - Kays, Roland
AU - Zhang, Zhi
AU - Ning, Guanghan
AU - Huang, Chen
AU - Han, Tony X.
AU - Millspaugh, Josh
AU - Forrester, Tavis
AU - McShea, William
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84962695859&partnerID=8YFLogxK
U2 - 10.1109/MCAS.2015.2510200
DO - 10.1109/MCAS.2015.2510200
M3 - Article
AN - SCOPUS:84962695859
SN - 1531-636X
VL - 16
SP - 73
EP - 86
JO - IEEE Circuits and Systems Magazine
JF - IEEE Circuits and Systems Magazine
IS - 1
M1 - 7404334
ER -