Back to articles
Articles
Volume: 32 | Article ID: art00003
Image
Small Object Bird Detection in Infrared Drone Videos Using Mask R-CNN Deep Learning
  DOI :  10.2352/ISSN.2470-1173.2020.8.IMAWM-085  Published OnlineJanuary 2020
Abstract

A reliable method to estimate population sizes of wild turkeys (Meleagris gallopavo) using unmanned aerial vehicles and thermal video imaging data collected at several field sites in Texas is described. Automating the data processing of airborne survey videos provides a fast and reproducible way to count wild turkeys for wildlife management and conservation. A deep learning semantic segmentation pipeline is developed to detect and count roosting Rio-Grande wild turkeys (M.g. intermedia) which appear as small faint objects in drone-based thermal IR videos. The proposed approach to detect roosting turkeys that appear as small objects, relies on Mask R-CNN, a deep architecture semantic segmentation algorithm. This is followed by a post-processing data association and filtering (DAF) process for counting the number of roosting birds. DAF was used to eliminate false positives like rocks and other small bright objects, which often have noisy detections across temporally adjacent video frames, that can be filtered using appearance association and distance-based gating across time. Transfer learning was used to train the Mask R-CNN network by initializing using ImageNet weights. Drone-based thermal IR videos are extremely challenging due to the complexity of the natural environment including weather effects, occlusion of birds, terrain, trees, complex tree shapes, rocks, water and thermal inversion. The transect videos were collected at night at several times and altitudes to optimize data collection opportunities without disturbing the roosting turkeys. Preliminary performance evaluation using 280 video frames is promising.

Subject Areas :
Views 135
Downloads 23
 articleview.views 135
 articleview.downloads 23
  Cite this article 

Yasmin M. Kassim, Michael E. Byrne, Cristy Burch, Kevin Mote, Jason Hardin, David R. Larsen, Kannappan Palaniappan, "Small Object Bird Detection in Infrared Drone Videos Using Mask R-CNN Deep Learningin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2020,  pp 85-1 - 85-8,  https://doi.org/10.2352/ISSN.2470-1173.2020.8.IMAWM-085

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2020
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA