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Camera Traps (or Wild Cams) enable the automatic collection of large quantities of image data. Biologists all over the world use camera traps to monitor biodiversity and population density of animal species. The computer vision community…

Computer Vision and Pattern Recognition · Computer Science 2019-07-18 Sara Beery , Dan Morris , Pietro Perona

Camera traps enable the automatic collection of large quantities of image data. Biologists all over the world use camera traps to monitor animal populations. We have recently been making strides towards automatic species classification in…

Computer Vision and Pattern Recognition · Computer Science 2020-04-23 Sara Beery , Elijah Cole , Arvi Gjoka

Camera traps enable the automatic collection of large quantities of image data. Ecologists use camera traps to monitor animal populations all over the world. In order to estimate the abundance of a species from camera trap data, ecologists…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Sara Beery , Arushi Agarwal , Elijah Cole , Vighnesh Birodkar

Camera trapping is increasingly used to monitor wildlife, but this technology typically requires extensive data annotation. Recently, deep learning has significantly advanced automatic wildlife recognition. However, current methods are…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Zhongqi Miao , Ziwei Liu , Kaitlyn M. Gaynor , Meredith S. Palmer , Stella X. Yu , Wayne M. Getz

Biodiversity conservation depends on accurate, up-to-date information about wildlife population distributions. Motion-activated cameras, also known as camera traps, are a critical tool for population surveys, as they are cheap and…

Machine Learning · Computer Science 2019-10-23 Mohammad Sadegh Norouzzadeh , Dan Morris , Sara Beery , Neel Joshi , Nebojsa Jojic , Jeff Clune

Build accurate DNN models requires training on large labeled, context specific datasets, especially those matching the target scenario. We believe advances in wireless localization, working in unison with cameras, can produce automated…

Computer Vision and Pattern Recognition · Computer Science 2018-10-11 Zhujun Xiao , Yanzi Zhu , Yuxin Chen , Ben Y. Zhao , Junchen Jiang , Haitao Zheng

Automatic species classification in camera traps would greatly help the biodiversity monitoring and species analysis in the earth. In order to accelerate the development of automatic species classification task, "Microsoft AI for Earth"…

Computer Vision and Pattern Recognition · Computer Science 2019-07-31 Abulikemu Abuduweili , Xin Wu , Xingchen Tao

Camera traps are important tools in animal ecology for biodiversity monitoring and conservation. However, their practical application is limited by issues such as poor generalization to new and unseen locations. Images are typically…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Vardaan Pahuja , Weidi Luo , Yu Gu , Cheng-Hao Tu , Hong-You Chen , Tanya Berger-Wolf , Charles Stewart , Song Gao , Wei-Lun Chao , Yu Su

The management of natural environments, whether for conservation or production, requires a deep understanding of wildlife. The number, location, and behavior of wild animals are among the main subjects of study in ecology and wildlife…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Federico Gonzalez , Leonel Viera , Rosina Soler , Lucila Chiarvetto Peralta , Matias Gel , Gimena Bustamante , Abril Montaldo , Brian Rigoni , Ignacio Perez

Camera-traps is a relatively new but already popular instrument in the estimation of abundance of non-identifiable animals. Although camera-traps are convenient in application, there remain both theoretical complications such as spatial…

Quantitative Methods · Quantitative Biology 2017-03-23 Evgeny Ivanko

Camera trap imagery has become an invaluable asset in contemporary wildlife surveillance, enabling researchers to observe and investigate the behaviors of wild animals. While existing methods rely solely on image data for classification,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Aslak Tøn , Ammar Ahmed , Ali Shariq Imran , Mohib Ullah , R. Muhammad Atif Azad

Wildlife camera trap images are being used extensively to investigate animal abundance, habitat associations, and behavior, which is complicated by the fact that experts must first classify the images manually. Artificial intelligence…

Computer Vision and Pattern Recognition · Computer Science 2023-08-03 Ludwig Bothmann , Lisa Wimmer , Omid Charrakh , Tobias Weber , Hendrik Edelhoff , Wibke Peters , Hien Nguyen , Caryl Benjamin , Annette Menzel

Camera traps are vital for large-scale biodiversity monitoring, yet accurate automated analysis remains challenging due to diverse deployment environments. While the computer vision community has mostly framed this challenge as cross-domain…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Sooyoung Jeon , Hongjie Tian , Lemeng Wang , Zheda Mai , Vidhi Bakshi , Jiacheng Hou , Ping Zhang , Arpita Chowdhury , Jianyang Gu , Wei-Lun Chao

People detection methods are highly sensitive to the perpetual occlusions among the targets. As multi-camera set-ups become more frequently encountered, joint exploitation of the across views information would allow for improved detection…

Computer Vision and Pattern Recognition · Computer Science 2017-07-31 Tatjana Chavdarova , Pierre Baqué , Stéphane Bouquet , Andrii Maksai , Cijo Jose , Louis Lettry , Pascal Fua , Luc Van Gool , François Fleuret

Biologists all over the world use camera traps to monitor biodiversity and wildlife population density. The computer vision community has been making strides towards automating the species classification challenge in camera traps, but it…

Computer Vision and Pattern Recognition · Computer Science 2019-07-17 Sara Beery , Dan Morris , Siyu Yang

The biodiversity crisis is still accelerating, despite increasing efforts by the international community. Estimating animal abundance is of critical importance to assess, for example, the consequences of land-use change and invasive species…

Computer Vision and Pattern Recognition · Computer Science 2021-12-23 Timm Haucke , Hjalmar S. Kühl , Jacqueline Hoyer , Volker Steinhage

Camera traps have transformed how ecologists study wildlife species distributions, activity patterns, and interspecific interactions. Although camera traps provide a cost-effective method for monitoring species, the time required for data…

Machine Learning · Computer Science 2022-02-07 Juliana Vélez , Paula J. Castiblanco-Camacho , Michael A. Tabak , Carl Chalmers , Paul Fergus , John Fieberg

Camera traps have long been used by wildlife researchers to monitor and study animal behavior, population dynamics, habitat use, and species diversity in a non-invasive and efficient manner. While data collection from the field has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Bernie Boscoe , Shawn Johnson , Andrea Osbon , Chandler Campbell , Karen Mager

Camera traps offer enormous new opportunities in ecological studies, but current automated image analysis methods often lack the contextual richness needed to support impactful conservation outcomes. Here we present an integrated approach…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Paul Fergus , Carl Chalmers , Naomi Matthews , Stuart Nixon , Andre Burger , Oliver Hartley , Chris Sutherland , Xavier Lambin , Steven Longmore , Serge Wich

Camera traps are a proven tool in biology and specifically biodiversity research. However, camera traps including depth estimation are not widely deployed, despite providing valuable context about the scene and facilitating the automation…

Computer Vision and Pattern Recognition · Computer Science 2021-02-11 Timm Haucke , Volker Steinhage
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