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Related papers: Efficient Pipeline for Camera Trap Image Review

200 papers

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

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

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

Classification and identification of wild animals for tracking and protection purposes has become increasingly important with the deterioration of the environment, and technology is the agent of change which augments this process with novel…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Sahil Faizal , Sanjay Sundaresan

Many creative ideas are being proposed for image sensor designs, and these may be useful in applications ranging from consumer photography to computer vision. To understand and evaluate each new design, we must create a corresponding image…

Computer Vision and Pattern Recognition · Computer Science 2017-10-11 Haomiao Jiang , Qiyuan Tian , Joyce Farrell , Brian Wandell

Monitoring plankton populations in situ is fundamental to preserve the aquatic ecosystem. Plankton microorganisms are in fact susceptible of minor environmental perturbations, that can reflect into consequent morphological and dynamical…

Computer Vision and Pattern Recognition · Computer Science 2022-09-15 Paolo Didier Alfano , Marco Rando , Marco Letizia , Francesca Odone , Lorenzo Rosasco , Vito Paolo Pastore

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

Camera traps have revolutionized the animal research of many species that were previously nearly impossible to observe due to their habitat or behavior. They are cameras generally fixed to a tree that take a short sequence of images when…

Computer Vision and Pattern Recognition · Computer Science 2022-08-31 Pierrick Pochelu , Clara Erard , Philippe Cordier , Serge G. Petiton , Bruno Conche

Biodiversity monitoring is crucial for tracking and counteracting adverse trends in population fluctuations. However, automatic recognition systems are rarely applied so far, and experts evaluate the generated data masses manually.…

Computer Vision and Pattern Recognition · Computer Science 2023-07-31 Dimitri Korsch , Paul Bodesheim , Joachim Denzler

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

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

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

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

The natural world is long-tailed: rare classes are observed orders of magnitudes less frequently than common ones, leading to highly-imbalanced data where rare classes can have only handfuls of examples. Learning from few examples is a…

Computer Vision and Pattern Recognition · Computer Science 2021-06-24 Edoardo Lanzini , Sara Beery

Deep learning (DL) algorithms are the state of the art in automated classification of wildlife camera trap images. The challenge is that the ecologist cannot know in advance how many images per species they need to collect for model…

Computer Vision and Pattern Recognition · Computer Science 2020-10-19 Saleh Shahinfar , Paul Meek , Greg Falzon

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

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

Preserving the number and diversity of insects is one of our society's most important goals in the area of environmental sustainability. A prerequisite for this is a systematic and up-scaled monitoring in order to detect correlations and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Danja Brandt , Martin Tschaikner , Teodor Chiaburu , Henning Schmidt , Ilona Schrimpf , Alexandra Stadel , Ingeborg E. Beckers , Frank Haußer

No publicly available, ML ready datasets exist for wildlife health conditions in camera trap imagery, creating a fundamental barrier to automated health screening. We present a pipeline for generating synthetic training images depicting…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 David Brundage

1) Biological collections house millions of specimens with digital images increasingly available through open-access platforms. However, most imaging protocols were developed for human interpretation without considering automated analysis…