Automated Whale Blow Detection in Infrared Video
Computer Vision and Pattern Recognition in Environmental Informatics
In this chapter, solutions to the problem of whale blow detection in infrared video are presented. The solutions are considered to be assistive technology that could help whale researchers to sift through hours or days of video without manual intervention. Video is captured from an elevated position along the shoreline using an infrared camera.
The presence of whales is inferred from the presence of blows detected in the video. In this chapter, three solutions are proposed for this problem. The first algorithm makes use of a neural network (multi-layer perceptron) for classification, the second uses fractal features and the third solution is using convolutional neural networks. The central idea of all the algorithms is to attempt and model the spatio-temporal characteristics of a whale blow accurately using appropriate mathematical models. We provide a detailed description and analysis of the proposed solutions, the challenges and some possible directions for future research.
Copyright © 2016, IGI Global
Place of Publication
Santhaseelan, Varun and Asari, Vijayan K., "Automated Whale Blow Detection in Infrared Video" (2016). Electrical and Computer Engineering Faculty Publications. 377.