18 papers · ranked by Valyu relevance
Jolyon Troscianko, Thomas A. O’Shea-Wheller, James Galloway, Kevin J. Gaston
Here we introduce BehaveAI, a biologically inspired video analysis framework that integrates static and motion information through a novel colour-from-motion encoding strategy. This method translates object movement – direction, speed, and acceleration – into colour gradients, enabling both human annotators and…
Anil Bayram Gogebakan, Filippo Marostica, Alessio Caviglia, Alessandro Savino + 1 more
Existing automotive event datasets rely on appearance-based annotations from frame pipelines, making them poorly suited for motion-aware event perception. We present a geometry-driven, annotation-free framework that classifies detected objects as static or independently moving by exploiting ego-motion structure…
Sameed Ur Rehman, Irshad Ullah, Wajahat Akbar, Altaf Hussain + 5 more
In dynamic settings such as security, autonomous driving, and robotics, effective motion detection and classification are crucial for accurate tracking amidst target and background movements. Traditional approaches, typically designed for static environments, face challenges in complex scenes with multiple types of…
Ayush Aggarwal, Rustam Stolkin, Naresh Marturi
—Autonomous robots operating in real-world environments encounter a variety of objects that can be both rigid and articulated in nature. Having knowledge of these specific object properties not only helps in designing appropriate manipulation strategies but also aids in developing reliable tracking and pose estimation…
Jagriti Chatterjee, Subhojyoti Chatterjee, Emil Gillett, Nikita Kovalenko + 2 more
for Machine Learned Classification of 3D Single-Particle Tracking Authors: Jagriti Chatterjee, Subhojyoti Chatterjee, Emil Gillett, Nikita Kovalenko, Dongyu Fan, Christy F. Landes Understanding diffusion in charged and crowded media is crucial for solving a wide range of biological and materials challenges. Classifying…
G. Nardi, M. Santos Sano, M. Bilay, A. Brelot + 2 more
Particle dynamics determine the orchestration of molecular signaling in cellular processes. A wide range of subdiffusive motions has been described at the cell interior and membrane, corresponding to different environmental constraints. However, the standard methods for motion analysis, embedded in a diffusion-based…
Arefeh Farahmandi, Gunnar Blohm
Humans recognize movements effortlessly, even from noisy and complex visual input. But what information in the stimulus allows humans to rapidly classify movements? No framework has systematically compared different strategies of movement analysis to address this question. Here, we used videos of 16 daily activities…
Senthilkumar Gopal
generation Authors: ['Senthilkumar Gopal'] Abstract—Human action recognition has been a topic of interest across multiple fields ranging from security to entertainment systems. Tracking the motion and identifying the action being performed on a real time basis is necessary for critical security systems. In…
Emahnuel Troisi Lopez, Roberta Minino, Mario De Luca, Francesco Tafuri + 3 more
automatic movement recognition is often used to support various fields such as clinical, sports, and security. To date, there is a lack of a classification feature that is both interpretable and not movement-specific, characteristics that would enhance generalization and adaptability. Previous studies on motion…
Xue Yang, Hanmin Sun, Yin Lyu, Yang Sun
Digital-image technology has broadened the creative space of dance, yet accurately capturing the semantic correspondence between low-level motion data and high-level dance key-points remains challenging, especially when labeled data are scarce. We aim to establish a lightweight, semi-supervised pipeline that can…
Andres Emilio Hurtado-Perez, Manuel Toledano-Ayala, Irving A. Cruz-Albarran, Alejandra Lopez-Zúñiga + 6 more
'Irving A. Cruz-Albarran' 'Alejandra Lopez-Zúñiga' 'Jesús Adrián Moreno-Perez' 'Alejandra Álvarez-López' 'Juvenal Rodriguez-Resendiz' 'Carlos A. Perez-Ramirez' 'Vicente Javier Clemente-Suárez' 'Ana Isabel Beltrán-Velasco'] This review provides an in-depth examination of the technologies and methods used for the…
Ali Ari, Pelin Atalan Efkere, Ecem Yıldız Çangur, Kamile Uzun Akkaya + 6 more
Background/Objectives: Assessment of infant General Movements (GMs) is essential for early detection of neurological disorders such as cerebral palsy, but current methods depend on expert interpretation. This study proposes an automated and interpretable framework for infant movement classification using pose-based…
Carl Harris, Kelly R. Finn, Peter U. Tse
The identification of behavior in video is a critical but time-consuming component in many areas of animal behavior research. Here, we introduce DeepAction, a deep learning-based toolbox for automatically annotating animal behavior in video. Our approach uses features extracted from raw video frames by a pretrained…
Ge Gao, Zhixin Li, Zhan Huan, Ying Chen + 6 more
'Bangwen Zhou' 'Chenhui Dong' 'Pubudu N. Pathirana' 'Matthew Joordens' 'Jeff Prevost'] With the rapid development of the computer and sensor field, inertial sensor data have been widely used in human activity recognition. At present, most relevant studies divide human activities into basic actions and transitional…
Yuki Fujita, Yuki Nagase, Sarthak Pathak, Alessandro Moro + 3 more
With the rapid expansion of global food demand, aquaculture has become a critical pillar for future food security. However, aquaculture systems remain highly vulnerable to pathogenic bacteria, and rapid identification of antagonistic microbes is essential for sustainable disease control. Conventional evaluation…
Feng Yang, Pan Liao, Di Wu, Bo Liu + 1 more
—In the realm of video analysis, the field of multiple object tracking (MOT) assumes paramount importance, with the motion state of objects—whether static or dynamic relative to the ground—holding practical significance across diverse scenarios. However, the extant literature exhibits a notable dearth in the…
Yuxiang Huang, John Zelek
—Identifying and segmenting moving objects from a moving monocular camera is difficult when there is unknown camera motion, different types of object motions and complex scene structures. To tackle these challenges, we take advantage of two popular branches of monocular motion segmentation approaches: point trajectory…
Pierre-Etienne Martin, J Benois-Pineau, R Péteri, A Zemmari + 1 more
3D convolutional networks is a good means to perform tasks such as video segmentation into coherent spatio-temporal chunks and classification of them with regard to a target taxonomy. In the chapter we are interested in the classification of continuous video takes with repeatable actions, such as strokes of table…