27 papers · ranked by Valyu relevance
Tristan Walter, Iain D Couzin
Automated visual tracking of animals is rapidly becoming an indispensable tool for the study of behavior. It offers a quantitative methodology by which organisms’ sensing and decision-making can be studied in a wide range of ecological contexts. Despite this, existing solutions tend to be challenging to deploy in…
Rubén Chao, Germán Macía-Vázquez, Eduardo Zalama, Jaime Gómez-García-Bermejo + 2 more
'Jaime Gómez-García-Bermejo' 'José-Ramón Perán' 'Vittorio M.N. Passaro'] The fruit fly Drosophila Melanogaster has become a model organism in the study of neurobiology and behavior patterns. The analysis of the way the fly moves and its behavior is of great scientific interest for research on aspects such as drug…
Nahlah Algethami, Sam Redfern
We propose a tracking-by-detection algorithm to track the movements of meeting participants from an overhead camera. An advantage of using overhead cameras is that all objects can typically be seen clearly, with little occlusion; however, detecting people from a wide-angle overhead view also poses challenges such as…
Mustansar Fiaz, Arif Mahmood, Soon Ki Jung
—Visual object tracking is an important computer vision problem with numerous real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. In this paper, we aim to extensively review the latest trends and advances in…
Allert I. Bijleveld, Frank van Maarseveen, Bas Denissen, Anne Dekinga + 9 more
Tracking animal movement is important for understanding how animals interact with their (changing) environment, and crucial for predicting and explaining how animals are affected by anthropogenic effects. The Wadden Sea is a UNESCO World Heritage Site and a region of global importance for millions of small shorebirds.…
Asaf Gal, Jonathan Saragosti, Daniel JC Kronauer, Gordon J Berman + 1 more
Recent years have seen a surge in methods to track and analyze animal behavior. Nevertheless, tracking individuals in closely interacting, group-living organisms remains a challenge. Here, we present anTraX, an algorithm and software package for high-throughput video tracking of color-tagged insects. anTraX combines…
James D Crall, Nick Gravish, Andrew M. Mountcastle, Stacey A. Combes
A fundamental challenge common to studies of animal movement, behavior, and ecology is the collection of high-quality datasets on spatial positions of animals as they change through space and time. Recent innovations in tracking technology have allowed researchers to collect large and highly accurate datasets on animal…
Zahra Soleimanitaleb, Mohammad Ali Keyvanrad
Object tracking is one of the foremost assignments in computer vision that has numerous commonsense applications such as traffic monitoring, robotics, autonomous vehicle tracking, and so on. Different researches have been tried later a long time, but since of diverse challenges such as occlusion, illumination…
Young Hwan Chang, Jeremy Linsley, Josh Lamstein, Jaslin Kalra + 7 more
Live-cell imaging is an important technique to study cell migration and proliferation as well as image-based profiling of drug perturbations over time. To gain biological insights from live-cell imaging data, it is necessary to identify individual cells, follow them over time and extract quantitative information.…
Jiawen Zhu, Zhi-Qi Cheng, Jun-Yan He, Chenyang Li + 4 more
'Huchuan Lu' 'Yifeng Geng' 'Xuansong Xie'] Advances in perception modeling have significantly improved the performance of object tracking. However, the current methods for specifying the target object in the initial frame are either by 1) using a box or mask template, or by 2) providing an explicit language…
Gergely Szabó, Paolo Bonaiuti, Andrea Ciliberto, András Horváth
The accurate tracking of live cells using video microscopy recordings remains a challenging task for popular state-ofthe-art image processing based object tracking methods. In recent years, several existing and new applications have attempted to integrate deep-learning based frameworks for this task, but most of them…
Mojtaba S. Fazli, Shannon Quinn
Gap to Biomedical Advancements Authors: ['Mojtaba S. Fazli' 'Shannon Quinn'] The authors would like to thank Prof. Silvia N.J. Moreno and Prof. Gary E. Ward for their collaboration on Toxoplasma projects. We also acknowledge Prof. Chakra Chennubhotla and Prof. Frederick D Quinn for their collaboration on OrNet project.…
Lars Haalck, Michael Mangan, Antoine Wystrach, Leo Clement + 2 more
'Barbara Webb' 'Benjamin Risse'] Quantifying the behavior of small animals traversing long distances in complex environments is one of the most difficult tracking scenarios for computer vision. Tiny and low-contrast foreground objects have to be localized in cluttered and dynamic scenes as well as trajectories…
Yudong Zhang, Dan Liu, Ge Yang
Accurate tracking of subcellular structures and cells under microscopy supports heavily the studies of their dynamic processes. However, the complex motion and the similar appearances of objects pose significant challenges in accurately identifying the identical object across multiple detection results without…
Jae-Min Shin, Yu-Sin Kim, Tae-Won Ban, Suna Choi + 2 more
'Jong-Yeol Ryu'] The need for drone traffic control management has emerged as the demand for drones increased. Particularly, in order to control unauthorized drones, the systems to detect and track drones have to be developed. In this paper, we propose the drone position tracking system using multiple Bluetooth low…
Katharina Löffler, Tim Scherr, Ralf Mikut
Automatic cell segmentation and tracking enables to gain quantitative insights into the processes driving cell migration. To investigate new data with minimal manual effort, cell tracking algorithms should be easy to apply and reduce manual curation time by providing automatic correction of segmentation errors. Current…
Yiru Jiang, Dezhi Han, Mingming Cui, Yuan Fan + 2 more
'Gemine Vivone'] In this paper, a cutting-edge video target tracking system is proposed, combining feature location and blockchain technology. The location method makes full use of feature registration and received trajectory correction signals to achieve high accuracy in tracking targets. The system leverages the…
Longtao Chen, Mingwu Ren, Long Wang
Aiming to address dense small object tracking, we propose an image-to-trajectory framework including tracking and detection, where Track-Oriented Multiple Hypothesis Tracking(TOMHT) is revised for tracking. Unlike common cases of multi-object tracking, merged detections and the greater number of objects make dense…
Weichao Li, Xi Li, Omar Elfarouk Bourahla, Fuxian Huang + 4 more
'Wei Liu' 'Zhiheng Wang' 'Hongmin Liu'] To tackle the above problem, we propose a joint discriminative learning scheme with the progressive multi-stage optimization policy of sample selection for robust visual tracking. The proposed scheme presents a novel time-weighted and detectionguided self-paced learning strategy…
Zhenghao Xi, Heping Liu, Huaping Liu, Bin Yang
To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer…
Mustansar Fiaz, Arif Mahmood, Sajid Javed, Soon Ki Jung
In recent years visual object tracking has become a very active research area. An increasing number of tracking algorithms are being proposed each year. It is because tracking has wide applications in various real world problems such as humancomputer interaction, autonomous vehicles, robotics, surveillance and security…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
Accurate prediction of battery behavior under different dynamic operating conditions is critical for both fundamental research and practical applications. However, the diversity of emerging materials and cell architectures presents significant challenges to the generalizability of conventional prognostic approaches.…
Authors not listed
Sequence-defined oligomers offer programmable molecular architectures with potential in data storage, authentication, and anticounterfeiting. However, their deployment in real-world materials has been constrained by their low scale, limited thermal resilience and the need for specialized analytical methods. Here we…
Authors not listed
The ability to track therapeutic cells is critical for advancing adoptive cell therapy (ACT). Positron emission tomography (PET) offers sensitive and quantitative imaging, yet improved cell radiolabeling strategies are sorely needed. We report a metabolic glycoengineering (MGE) approach that installs azide moieties on…
Authors not listed
This paper presents GLAS (Git-based Lab Automated Scheduler or Get Lab Automation Simplified), an open-source, robust, and highly expandable Git-based architecture designed for laboratory automation. GLAS can be deployed in both partially and fully automated experimental science laboratories, enabling the development…
Peter Kraus, Edan Bainglass, Francisco F. Ramirez, Enea Svaluto-Ferro + 7 more
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We…