A computer vision approach to classification of birds in flight from video sequences

Atanbori, John, Duan, Wenting, Appiah, Kofi , Murray, John and Dickinson, Patrick (2015) A computer vision approach to classification of birds in flight from video sequences. In: BMVC 2015, 07-10 Sept 2015, Swansea, UK.

18535 Impact Summary_WDUAN.pdf

Request a copy
18535 Atanbori MVAB2015.pdf
[img] PDF
18535 Impact Summary_WDUAN.pdf - Supplemental Material
Restricted to Repository staff only

18535 Atanbori MVAB2015.pdf - Whole Document

Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


Bird populations are an important bio-indicator, ; so collecting reliable data is useful for ecologists helping conserve and manage fragile ecosystems. However, existing manual monitoring methods are labour-intensive, time-consuming, and error-prone. The aim of our work is to develop a reliable system, capable of automatically classifying individual bird species in flight from videos. This is challenging, but appropriate for use in the field, since there is often a requirement to identify in flight, rather than when stationary. We present our work in progress which uses combined appearance and motion features to classify and present experimental results across seven species using Normal Bayes classifier with majority voting and achieving a classification rate of 86%.

Keywords:Fine-grained classification, Computer vision, Ecology, Flying Bird Species, Motion and Appearance features, bmjholiday
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
Related URLs:
ID Code:18535
Deposited On:02 Sep 2015 10:54

Repository Staff Only: item control page