The emerging field of graph signal processing for moving object segmentation

JH Giraldo, S Javed, M Sultana, SK Jung… - … workshop on frontiers of …, 2021 - Springer
Abstract Moving Object Segmentation (MOS) is an important topic in computer vision. MOS
becomes a challenging problem in the presence of dynamic background and moving …

Graph moving object segmentation

JH Giraldo, S Javed… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Moving Object Segmentation (MOS) is a fundamental task in computer vision. Due to
undesirable variations in the background scene, MOS becomes very challenging for static …

Reconstruction of time-varying graph signals via Sobolev smoothness

JH Giraldo, A Mahmood… - … on Signal and …, 2022 - ieeexplore.ieee.org
Graph Signal Processing (GSP) is an emerging research field that extends the concepts of
digital signal processing to graphs. GSP has numerous applications in different areas such …

Graph CNN for moving object detection in complex environments from unseen videos

JH Giraldo, S Javed, N Werghi… - Proceedings of the …, 2021 - openaccess.thecvf.com
Abstract Moving Object Detection (MOD) is a fundamental step for many computer vision
applications. MOD becomes very challenging when a video sequence captured from a static …

Context-aware sampling of large networks via graph representation learning

Z Zhou, C Shi, X Shen, L Cai, H Wang… - … on Visualization and …, 2020 - ieeexplore.ieee.org
Numerous sampling strategies have been proposed to simplify large-scale networks for
highly readable visualizations. It is of great challenge to preserve contextual structures …

Graphon pooling for reducing dimensionality of signals and convolutional operators on graphs

A Parada-Mayorga, Z Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article we propose a pooling approach for convolutional information processing on
graphs relying on the theory of graphons and limits of dense graph sequences. We present …

GraphBGS: Background subtraction via recovery of graph signals

JH Giraldo, T Bouwmans - 2020 25th International Conference …, 2021 - ieeexplore.ieee.org
Background subtraction is a fundamental preprocessing task in computer vision. This task
becomes challenging in real scenarios due to variations in the background for both static …

Joint sampling and reconstruction of time-varying signals over directed graphs

Z Xiao, H Fang, S Tomasin, G Mateos… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vertex-domain and temporal-domain smoothness of time-varying graph signals are cardinal
properties that can be exploited for effective graph signal reconstruction from limited …

A user-driven sampling model for large-scale geographical point data visualization via convolutional neural networks

Z Zhou, F Zheng, J Wen, Y Chen, X Li… - … on Human-Machine …, 2023 - ieeexplore.ieee.org
Numerous sampling strategies have been proposed to reduce the visual clutter of large-
scale geographical point data visualization, which focus on the preservation of original data …

Parallel graph signal processing: Sampling and reconstruction

D Dapena, DL Lau, GR Arce - IEEE Transactions on Signal and …, 2023 - ieeexplore.ieee.org
Graph signal processing (GSP) extends classical signal processing methods to analyzing
signals supported over irregular grids represented by graphs. Within the scope of GSP …