Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate.
This presentation will discuss recent developments in unmanned aerial vehicles (UAV) commonly known as drones , artificial intelligence and miniaturized RGB, and thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. I disucss thermal image and RGB acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest, ocean or open areas.
The methods are demonstrated on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.