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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

Event cameras provide a natural and data efficient representation of visual information, motivating novel computational strategies towards extracting visual information. Inspired by the biological vision system, we propose a behavior driven…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Nan Cai , Pia Bideau

Distance estimation from vision is fundamental for a myriad of robotic applications such as navigation, manipulation, and planning. Inspired by the mammal's visual system, which gazes at specific objects, we develop two novel constraints…

Robotics · Computer Science 2023-03-08 Levi Burner , Nitin J. Sanket , Cornelia Fermüller , Yiannis Aloimonos

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

This study revisits the findings of Carl et al., who evaluated the pre-trained Google Inception-ResNet-v2 model for automated detection of European wild mammal species in camera trap images. To assess the reproducibility and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Tobias Abraham Haider

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

Understanding how biological communities respond to environmental changes is a key challenge in ecology and ecosystem management. The apparent decline of insect populations necessitates more biomonitoring but the time-consuming sorting and…

Automatic detection of animals that have strayed into human inhabited areas has important security and road safety applications. This paper attempts to solve this problem using deep learning techniques from a variety of computer vision…

Computer Vision and Pattern Recognition · Computer Science 2020-01-15 Abhineet Singh , Marcin Pietrasik , Gabriell Natha , Nehla Ghouaiel , Ken Brizel , Nilanjan Ray

Animal Pose Estimation and Tracking (APT) is a critical task in detecting and monitoring the keypoints of animals across a series of video frames, which is essential for understanding animal behavior. Past works relating to animals have…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yuxiang Yang , Yingqi Deng , Yufei Xu , Jing Zhang

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 (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

Wildlife monitoring is crucial for studying biodiversity loss and climate change. Camera trap images provide a non-intrusive method for analyzing animal populations and identifying ecological patterns over time. However, manual analysis is…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Julian D. Santamaria , Claudia Isaza , Jhony H. Giraldo

Field-captured video facilitates detailed studies of spatio-temporal aspects of animal locomotion, decision-making and environmental interactions including predator-prey relationships and habitat utilisation. But even though data capture is…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Malika Nisal Ratnayake , Lex Gallon , Adel N. Toosi , Alan Dorin

Accurate pest population monitoring and tracking their dynamic changes are crucial for precision agriculture decision-making. A common limitation in existing vision-based automatic pest counting research is that models are typically…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Xumin Gao , Mark Stevens , Grzegorz Cielniak

In modern production facilities industrial robots and humans are supposed to interact sharing a common working area. In order to avoid collisions, the distances between objects need to be measured conservatively which can be done by a…

Computer Vision and Pattern Recognition · Computer Science 2011-05-18 Maria Hänel , Stefan Kuhn , Dominik Henrich , Lars Grüne , Jürgen Pannek

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

Estimating the distance to objects is crucial for autonomous vehicles when using depth sensors is not possible. In this case, the distance has to be estimated from on-board mounted RGB cameras, which is a complex task especially in…

Computer Vision and Pattern Recognition · Computer Science 2022-07-04 Michaël Fonder , Damien Ernst , Marc Van Droogenbroeck

Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging devices. These new technologies and the data they generate hold…

Visuals captured by high-flying aerial drones are increasingly used to assess biodiversity and animal population dynamics around the globe. Yet, challenging acquisition scenarios and tiny animal depictions in airborne imagery, despite…

Computer Vision and Pattern Recognition · Computer Science 2021-11-15 Mowen Xue , Theo Greenslade , Majid Mirmehdi , Tilo Burghardt

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