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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 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 are a valuable tool for studying biodiversity, but research using this data is limited by the speed of human annotation. With the vast amounts of data now available it is imperative that we develop automatic solutions for…

Computer Vision and Pattern Recognition · Computer Science 2019-04-26 Sara Beery , Grant van Horn , Oisin Mac Aodha , Pietro Perona

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

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

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 used by ecologists globally as an efficient and non-invasive method to monitor animals. While it is time-consuming to manually label the collected images, recent advances in deep learning and computer vision has made it…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Gareth Lamb , Ching Hei Lo , Jin Wu , Calvin K. F. Lee

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

Understanding the abundance of a species is the first step towards understanding both its long-term sustainability and the impact that we may be having upon it. Ecologists use camera traps to remotely survey for the presence of specific…

Computer Vision and Pattern Recognition · Computer Science 2021-11-29 Ryan Curry , Cameron Trotter , Andrew Stephen McGough

It is desirable for detection and classification algorithms to generalize to unfamiliar environments, but suitable benchmarks for quantitatively studying this phenomenon are not yet available. We present a dataset designed to measure…

Computer Vision and Pattern Recognition · Computer Science 2019-12-13 Sara Beery , Grant van Horn , Pietro Perona

The ability of a researcher to re-identify (re-ID) an individual animal upon re-encounter is fundamental for addressing a broad range of questions in the study of ecosystem function, community and population dynamics, and behavioural…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Stefan Schneider , Graham W. Taylor , Stefan S. Linquist , Stefan C. Kremer

Having accurate, detailed, and up-to-date information about the location and behavior of animals in the wild would revolutionize our ability to study and conserve ecosystems. We investigate the ability to automatically, accurately, and…

Computer Vision and Pattern Recognition · Computer Science 2017-11-17 Mohammed Sadegh Norouzzadeh , Anh Nguyen , Margaret Kosmala , Ali Swanson , Meredith Palmer , Craig Packer , Jeff Clune

Non intrusive monitoring of animals in the wild is possible using camera trapping framework, which uses cameras triggered by sensors to take a burst of images of animals in their habitat. However camera trapping framework produces a high…

Computer Vision and Pattern Recognition · Computer Science 2016-03-23 Alexander Gomez , Augusto Salazar , Francisco Vargas

Photographs of wild animals in their natural habitats can be recorded unobtrusively via cameras that are triggered by motion nearby. The installation of such camera traps is becoming increasingly common across the world. Although this is a…

Computer Vision and Pattern Recognition · Computer Science 2020-06-18 Rita Pucci , Jitendra Shankaraiah , Devcharan Jathanna , Ullas Karanth , Kartic Subr

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

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

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

Wildlife monitoring is crucial to nature conservation and has been done by manual observations from motion-triggered camera traps deployed in the field. Widespread adoption of such in-situ sensors has resulted in unprecedented data volumes…

Computer Vision and Pattern Recognition · Computer Science 2020-09-25 Sayali Kulkarni , Tomer Gadot , Chen Luo , Tanya Birch , Eric Fegraus
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