干旱区生态环境知识资源中心(Arid): Desert bighorn sheep (Ovis canadensis) recognition from camera traps based on learned features

Arid

DOI	10.1016/j.ecoinf.2021.101328
	Desert bighorn sheep (Ovis canadensis) recognition from camera traps based on learned features
	Vargas-Felipe, Manuel; Pellegrin, Luis; Guevara-Carrizales, Aldo A.; Lopez-Monroy, A. Pastor; Escalante, Hugo Jair; Gonzalez-Fraga, Jose A.
通讯作者	Pellegrin, L (corresponding author), Univ Autonoma Baja California UABC, Fac Sci, Ensenada, Baja California, Mexico.
来源期刊	ECOLOGICAL INFORMATICS
ISSN	1574-9541
EISSN	1878-0512
出版年	2021
卷号	64
英文摘要	Monitoring wildlife in geographical areas is essential for the conservation of the biological heritage. At present, the strenuous task of animal observation on-site has been mitigated with the use of camera traps. The information gathered by these devices comprises a sequence of images, which are triggered by motion or heat, and enables the monitoring of several geographical areas at the same time without perturbing the fauna. Notwithstanding the advances of these kind of monitoring approaches, the captured images still must be manually classified, becoming into an expensive process. This paper describes an automatic methodology for labeling images captured with camera traps as a support tool for animal behaviour analysis. Specifically, we focus on the analysis of the Ovis canadensis better known as desert bighorn sheep, a species that inhabits in northwestern Mexico, USA and Canada. The importance of this species lies in that it is an emblematic one, of great historical, cultural and social value. We adopted a methodology based on a residual neural network (ResNet) as feature extractor and standard models for the classification of images depicting species of interest. The method is built (trained) and evaluated on realistic images captured by camera traps in the field. We achieve classification performances ranging from 89% for a multiclass classification setting (7 classes associated to the animal of interest) to 99% in a binary classification scenario (presence vs. absence of the species). The collected data set, model and extracted features are publicly available under request. We foresee the released data set and the proposed solution will boost research on the analysis of this species.
英文关键词	Desert bighorn sheep Deep learning Convolutional neural networks Image classification Species recognition Monitoring Camera traps
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000691763100004
WOS关键词	ANIMALS
WOS类目	Ecology
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/363014
作者单位	[Vargas-Felipe, Manuel; Pellegrin, Luis; Guevara-Carrizales, Aldo A.; Gonzalez-Fraga, Jose A.] Univ Autonoma Baja California UABC, Fac Sci, Ensenada, Baja California, Mexico; [Lopez-Monroy, A. Pastor] Ctr Invest Matemat CIMAT AC, Comp Sci Dept, Guanajuato, Mexico; [Escalante, Hugo Jair] Inst Nacl Astrofis Opt & Elect INAOE, Comp Sci Dept, Cholula, Mexico
推荐引用方式 GB/T 7714	Vargas-Felipe, Manuel,Pellegrin, Luis,Guevara-Carrizales, Aldo A.,et al. Desert bighorn sheep (Ovis canadensis) recognition from camera traps based on learned features[J],2021,64.
APA	Vargas-Felipe, Manuel,Pellegrin, Luis,Guevara-Carrizales, Aldo A.,Lopez-Monroy, A. Pastor,Escalante, Hugo Jair,&Gonzalez-Fraga, Jose A..(2021).Desert bighorn sheep (Ovis canadensis) recognition from camera traps based on learned features.ECOLOGICAL INFORMATICS,64.
MLA	Vargas-Felipe, Manuel,et al."Desert bighorn sheep (Ovis canadensis) recognition from camera traps based on learned features".ECOLOGICAL INFORMATICS 64(2021).