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Monitoring animal populations is crucial for assessing the health of ecosystems. Traditional methods, which require extensive fieldwork, are increasingly being supplemented by time-lapse camera-trap imagery combined with an automatic…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Marcus Jenkins , Kirsty A. Franklin , Malcolm A. C. Nicoll , Nik C. Cole , Kevin Ruhomaun , Vikash Tatayah , Michal Mackiewicz

Camera traps have become a common tool for wildlife monitoring efforts in ecological research and biodiversity conservation. Wildlife classification models have benefited from the increase in wildlife visual data. These models reach high…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Mufhumudzi Muthivhi , Jiahao Huo , Fredrik Gustafsson , Terence L. van Zyl

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

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

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

The development and application of modern technology is an essential basis for the efficient monitoring of species in natural habitats and landscapes to trace the development of ecosystems, species communities, and populations, and to…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Timm Haucke , Hjalmar S. Kühl , Volker Steinhage

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

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

Birds are important indicators for monitoring both biodiversity and habitat health; they also play a crucial role in ecosystem management. Decline in bird populations can result in reduced eco-system services, including seed dispersal,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-04 Carl Chalmers , Paul Fergus , Serge Wich , Steven N Longmore , Naomi Davies Walsh , Philip Stephens , Chris Sutherland , Naomi Matthews , Jens Mudde , Amira Nuseibeh

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 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 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 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 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

The continuous growth of the global human population is leading to the expansion of human habitats, resulting in decreasing wildlife spaces and increasing human-wildlife interactions. These interactions can range from minor disturbances,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jens Dede , Anna Förster

Camera traps have become a core tool in ecological research, enabling large-scale, noninvasive monitoring of wildlife populations and behavior. By automatically recording animals as they pass within view, these devices generate massive…

Applications · Statistics 2026-05-14 Adira Cohen , Erin M. Schliep , Roland Kays , Mohammad Alyetama , Matthew Snider

The segmentation and classification of animals from camera-trap images is due to the conditions under which the images are taken, a difficult task. This work presents a method for classifying and segmenting mammal genera from camera-trap…

Computer Vision and Pattern Recognition · Computer Science 2017-05-09 Jhony-Heriberto Giraldo-Zuluaga , Augusto Salazar , Alexander Gomez , Angélica Diaz-Pulido

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

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

Deep learning methods for computer vision tasks show promise for automating the data analysis of camera trap images. Ecological camera traps are a common approach for monitoring an ecosystem's animal population, as they provide continual…

Computer Vision and Pattern Recognition · Computer Science 2018-03-30 Stefan Schneider , Graham W. Taylor , Stefan C. Kremer
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