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相关论文: Efficient Pipeline for Camera Trap Image Review

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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…

计算机视觉与模式识别 · 计算机科学 2025-07-22 Bernie Boscoe , Shawn Johnson , Andrea Osbon , Chandler Campbell , Karen Mager

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…

机器学习 · 计算机科学 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…

计算机视觉与模式识别 · 计算机科学 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…

计算机视觉与模式识别 · 计算机科学 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…

计算机视觉与模式识别 · 计算机科学 2020-04-23 Sara Beery , Elijah Cole , Arvi Gjoka

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…

计算机视觉与模式识别 · 计算机科学 2024-03-26 Gareth Lamb , Ching Hei Lo , Jin Wu , Calvin K. F. Lee

A new open-source image processing pipeline for analyzing camera trap time-lapse recordings is described. This pipeline includes machine learning models to assist human-in-the-loop video segmentation and animal re-identification. We present…

计算机视觉与模式识别 · 计算机科学 2022-06-13 Michael L. Hilton , Mark T. Yamane , Leah M. Knezevich

Climate change and other anthropogenic factors have led to a catastrophic decline in insects, endangering both biodiversity and the ecosystem services on which human society depends. Data on insect abundance, however, remains woefully…

计算机视觉与模式识别 · 计算机科学 2024-06-21 Aditya Jain , Fagner Cunha , Michael Bunsen , Léonard Pasi , Anna Viklund , Maxim Larrivée , David Rolnick

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…

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…

计算机视觉与模式识别 · 计算机科学 2021-12-23 Timm Haucke , Hjalmar S. Kühl , Jacqueline Hoyer , Volker Steinhage

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…

计算机视觉与模式识别 · 计算机科学 2026-03-24 Sooyoung Jeon , Hongjie Tian , Lemeng Wang , Zheda Mai , Vidhi Bakshi , Jiacheng Hou , Ping Zhang , Arpita Chowdhury , Jianyang Gu , Wei-Lun Chao

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,…

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…

计算机视觉与模式识别 · 计算机科学 2016-03-23 Alexander Gomez , Augusto Salazar , Francisco Vargas

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"…

计算机视觉与模式识别 · 计算机科学 2019-07-31 Abulikemu Abuduweili , Xin Wu , Xingchen Tao

Monitoring wildlife through camera traps produces a massive amount of images, whose a significant portion does not contain animals, being later discarded. Embedding deep learning models to identify animals and filter these images directly…

计算机视觉与模式识别 · 计算机科学 2021-04-20 Fagner Cunha , Eulanda M. dos Santos , Raimundo Barreto , Juan G. Colonna

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…

计算机视觉与模式识别 · 计算机科学 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

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…

计算机视觉与模式识别 · 计算机科学 2019-04-26 Sara Beery , Grant van Horn , Oisin Mac Aodha , Pietro Perona

Camera Traps are extensively used to observe wildlife in their natural habitat without disturbing the ecosystem. This could help in the early detection of natural or human threats to animals, and help towards ecological conservation.…

计算机视觉与模式识别 · 计算机科学 2020-06-09 Bhuvan Malladihalli Shashidhara , Darshan Mehta , Yash Kale , Dan Morris , Megan Hazen

This paper introduces an automated vision system for animal detection in trail-camera images taken from a field under the administration of the Texas Parks and Wildlife Department. As traditional wildlife counting techniques are intrusive…

计算机视觉与模式识别 · 计算机科学 2021-03-09 Golnaz Moallem , Don D. Pathirage , Joel Reznick , James Gallagher , Hamed Sari-Sarraf

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…

计算机视觉与模式识别 · 计算机科学 2018-11-20 Stefan Schneider , Graham W. Taylor , Stefan S. Linquist , Stefan C. Kremer
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