Automatic classification of flying bird species using computer vision techniques

ATANBORI, John, DUAN, Wenting, MURRAY, John, APPIAH, Kofi and DICKINSON, Patrick (2016). Automatic classification of flying bird species using computer vision techniques. Pattern Recognition Letters, 81, 53 - 62.

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Abstract Bird populations are identified as important biodiversity indicators, so collecting reliable population data is important to ecologists and scientists. However, existing manual monitoring methods are labour-intensive, time-consuming, and potentially error prone. The aim of our work is to develop a reliable automated system, capable of classifying the species of individual birds, during flight, using video data. This is challenging, but appropriate for use in the field, since there is often a requirement to identify in flight, rather than while stationary. We present our work, which uses a new and rich set of appearance features for classification from video. We also introduce motion features including curvature and wing beat frequency. Combined with Normal Bayes classifier and a Support Vector Machine classifier, we present experimental evaluations of our appearance and motion features across a data set comprising seven species. Using our appearance feature set alone we achieved a classification rate of 92 and 89 (using Normal Bayes and SVM classifiers respectively) which significantly outperforms a recent comparable state-of-the-art system. Using motion features alone we achieved a lower-classification rate, but motivate our on-going work which we seeks to combine these appearance and motion feature to achieve even more robust classification.

Item Type: Article
Uncontrolled Keywords: Fine-grained classification, Computer vision, Ecology, Bird species, Motion features, Appearance features
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Identification Number:
Page Range: 53 - 62
Depositing User: Kofi Appiah
Date Deposited: 17 Jan 2018 15:36
Last Modified: 18 Mar 2021 02:20

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