TY - GEN
T1 - A Comparison of Feature Detectors for Underwater Sonar Imagery
AU - Tueller, Peter
AU - Kastner, Ryan
AU - Diamant, Roee
N1 - Publisher Copyright: © 2018 IEEE.
PY - 2019/1/7
Y1 - 2019/1/7
N2 - In this work we compare the performance of seven popular feature detection algorithms on a synthetic sonar image dataset. The dataset consists of a single mine-like object (MLO) superimposed on three different backgrounds: grass, sand ripple, and sand. We explore the performance of Harris, Shi-Tomasi, SIFT, SURF, STAR, FAST, and ORB on each of these backgrounds, and all the backgrounds at once by training an SVM classifier. Performance is evaluated with ROC curves by comparing the number of correctly identified features belonging to objects (True Positives) and the number of incorrectly identified features belonging to background noise (False Positives).
AB - In this work we compare the performance of seven popular feature detection algorithms on a synthetic sonar image dataset. The dataset consists of a single mine-like object (MLO) superimposed on three different backgrounds: grass, sand ripple, and sand. We explore the performance of Harris, Shi-Tomasi, SIFT, SURF, STAR, FAST, and ORB on each of these backgrounds, and all the backgrounds at once by training an SVM classifier. Performance is evaluated with ROC curves by comparing the number of correctly identified features belonging to objects (True Positives) and the number of incorrectly identified features belonging to background noise (False Positives).
KW - Feature detection
KW - Sonar
KW - Visual odometry
UR - http://www.scopus.com/inward/record.url?scp=85061814413&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/OCEANS.2018.8604786
DO - https://doi.org/10.1109/OCEANS.2018.8604786
M3 - Conference contribution
T3 - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018
BT - OCEANS 2018 MTS/IEEE Charleston, OCEAN 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - OCEANS 2018 MTS/IEEE Charleston, OCEANS 2018
Y2 - 22 October 2018 through 25 October 2018
ER -