Learning Temporal Distribution and Spatial Correlation Towards Universal Moving Object Segmentation
The goal of moving object segmentation is separating moving objects from stationary
backgrounds in videos. One major challenge in this problem is how to develop a universal …
backgrounds in videos. One major challenge in this problem is how to develop a universal …
Learning Spatial-Temporal Regularized Tensor Sparse RPCA for Background Subtraction
Video background subtraction is one of the fundamental problems in computer vision that
aims to segment all moving objects. Robust principal component analysis has been …
aims to segment all moving objects. Robust principal component analysis has been …
A Multi-Scale Contrast Preserving Encoder-Decoder Architecture for Local Change Detection From Thermal Video Scenes
This article presents a new deep-learning architecture based on an encoder-decoder
framework that retains contrast while performing background subtraction (BS) on thermal …
framework that retains contrast while performing background subtraction (BS) on thermal …
Learning Temporal Distribution and Spatial Correlation Towards Universal Moving Object Segmentation
The goal of moving object segmentation is separating moving objects from stationary
backgrounds in videos. One major challenge in this problem is how to develop a universal …
backgrounds in videos. One major challenge in this problem is how to develop a universal …
Moving Object Detection in Freely Moving Camera via Global Motion Compensation and Local Spatial Information Fusion
Z Chen, R Zhao, X Guo, J Xie, X Han - Sensors, 2024 - mdpi.com
Motion object detection (MOD) with freely moving cameras is a challenging task in computer
vision. To extract moving objects, most studies have focused on the difference in motion …
vision. To extract moving objects, most studies have focused on the difference in motion …
A ResNet-101 deep learning framework induced transfer learning strategy for moving object detection
Background subtraction is a crucial stage in many visual surveillance systems. The prime
objective of any such system is to detect moving objects such that the system could be …
objective of any such system is to detect moving objects such that the system could be …
Highway spillage detection using an improved STPM anomaly detection network from a surveillance perspective
H Liang, H Song, S Zhang, Y Bu - Applied Intelligence, 2025 - Springer
Spillages may cause traffic congestion and incidents and seriously affect the efficiency of
traffic operation. Due to the changeable shape and scale of a spill on a highway, the location …
traffic operation. Due to the changeable shape and scale of a spill on a highway, the location …
BgSubNet: Robust Semi-Supervised Background Subtraction In Realistic Scenes
Background subtraction (BgS) is a problem for handling pixel-level identification of changing
or moving entities in the field of view of a static camera system. Recent works have …
or moving entities in the field of view of a static camera system. Recent works have …
net: Global–Local Semantics Coupled Network for scene-specific video foreground extraction with less supervision
T Ruan, S Wei, Y Zhao, B Guo, Z Yu - Pattern Analysis and Applications, 2023 - Springer
Video foreground extraction has been widely applied to quantitative fields and attracts great
attention all over the world. Nevertheless, the performance of a such method can be easily …
attention all over the world. Nevertheless, the performance of a such method can be easily …
Background subtraction for video sequence using deep neural network
Y Dai, L Yang - Multimedia Tools and Applications, 2024 - Springer
Background subtraction aims to extract moving objects from a video sequence which is a
prerequisite for high-level surveillance video analysis. There are many challenges triggered …
prerequisite for high-level surveillance video analysis. There are many challenges triggered …