Automatic detection of bumblebees using video analysis

Willy Azarcoya-Cabiedes; Pablo Vera-Alfaro; Alfonso Torres-Ruiz; Joaquín Salas-Rodríguez

doi:10.15446/dyna.v81n187.40475

Automatic detection of bumblebees using video analysis

Translated title of the contribution: Automatic detection of bumblebees using video analysis

Willy Azarcoya-Cabiedes, Pablo Vera-Alfaro, Alfonso Torres-Ruiz, Joaquín Salas-Rodríguez

Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada (CICATA), Unidad Querétaro

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

In this document, we explore and develop techniques to automatically detect bumblebees flying freely inside a greenhouse, where illumination conditions are left unconstrained, and no artifact is used on their bodies. Specifically, we compare a Viola-Jones classifier and a Support Vector Machine (SVM) classifier to detect the presence of bumblebees. Our results show that the latter has a better classification performance.

Translated title of the contribution	Automatic detection of bumblebees using video analysis
Original language	English
Pages (from-to)	81-84
Number of pages	4
Journal	DYNA (Colombia)
Volume	81
Issue number	187
DOIs	https://doi.org/10.15446/dyna.v81n187.40475
State	Published - 1 Oct 2014

Keywords

Bumblebee detection
Support vector machine classifier
Viola-Jones classifier

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10.15446/dyna.v81n187.40475

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keywords = "Bumblebee detection, Support vector machine classifier, Viola-Jones classifier",

author = "Willy Azarcoya-Cabiedes and Pablo Vera-Alfaro and Alfonso Torres-Ruiz and Joaqu{\'i}n Salas-Rodr{\'i}guez",

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AU - Azarcoya-Cabiedes, Willy

AU - Vera-Alfaro, Pablo

AU - Torres-Ruiz, Alfonso

AU - Salas-Rodríguez, Joaquín

N1 - Publisher Copyright: © The author; licensee Universidad Nacional de Colombia.

PY - 2014/10/1

Y1 - 2014/10/1

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AB - In this document, we explore and develop techniques to automatically detect bumblebees flying freely inside a greenhouse, where illumination conditions are left unconstrained, and no artifact is used on their bodies. Specifically, we compare a Viola-Jones classifier and a Support Vector Machine (SVM) classifier to detect the presence of bumblebees. Our results show that the latter has a better classification performance.

KW - Bumblebee detection

KW - Support vector machine classifier

KW - Viola-Jones classifier

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DO - 10.15446/dyna.v81n187.40475

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JO - DYNA (Colombia)

JF - DYNA (Colombia)

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ER -

Automatic detection of bumblebees using video analysis

Abstract

Keywords

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