e-journal

Automatic Bird Species Detection From Crowd Sourced Videos

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To assist nature observation, we develop two algorithms to enable automatic bird species filtering using crowd sourced videos as inputs where camera motion and parameters are often unknown. The first algorithm recognizes the time series of salient extremities, which is the inter-wing tip distance (IWTD), from motion segmented bird contours. To analyze the feasibility of the proposed algorithm, we derive the probability that the salient extremity can be recognized from a video captured by an arbitrary camera with unknown parameters. We also prove that the periodicity of the IWTD in the image is the same as
the wingbeat frequency in the 3D space regardless of camera parameters with the exception of ignorable degenerated cases. Therefore, the second algorithm applies Fast Fourier Transform to the series and classifies bird species using likelihood ratios. The algorithm outputs a ranked list of likelihood of candidate species. Experiment results validate our analysis and show that the algorithm is very robust to segmentation error and data loss up to 30%. Note to Practitioners—For field biologists, automation is still a recent concept in data acquisition and analysis. The two proposed algorithms enable automatic data analysis for crowd sourced videos, which often contain rich information about large habitats
across multiple bird species. In fact, the bottleneck in utilizing these big video data is the time it takes to analyze them. Since crowd sourced videos are often taken by untrained amateurs with
unknown camera motion and parameters. The videos are often taken at different and challenging lighting conditions because birds are often active at twilight time. Emphasizing on robustness and sensitivity instead of selectivity, our algorithm design takes the aforementioned factors into account and only utilizes motion information in the detection process to facilitate wide application. Index Terms—Automation, bird species detection, video data analysis.

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Ketersediaan

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Informasi Detail

Judul Seri

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING

No. Panggil

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Penerbit

: ., 2014

Deskripsi Fisik

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 11, NO. 2, APRIL 2014

Bahasa

English

ISBN/ISSN

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Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

VOL. 11, NO. 2

Subjek

TEKNIK

Info Detail Spesifik

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Pernyataan Tanggungjawab

yuli/agus

Versi lain/terkait

Lampiran Berkas

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