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Anomaly Detection via Local Coordinate Factorization and Spatio-Temporal Pyramid
[chapter]
2015
Lecture Notes in Computer Science
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Specifically, Local Coordinate Factorization is utilized to tell whether a spatio-temporal video volume (STV) belongs to an anomaly, which can effectively detect spatial, temporal and spatio-temporal anomalies ...
In this paper, we propose an efficient anomaly detection approach which can perform both real-time and multi-scale detection. Our approach can handle the change of background. ...
Furthermore, the Spatio-temporal Pyramid allow us to perform multi-scale detection. ...
doi:10.1007/978-3-319-16814-2_5
fatcat:opw6ez5mjrb6jpipzbfoo54guq
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection in Distribution Networks
[article]
2018
arXiv
pre-print
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First, spatio-temporal matrix for each feeder in the distribution network is formulated and the spectrum of its covariance matrix is analyzed. ...
By leveraging the data, this paper proposes a spatio-temporal correlation analysis approach for anomaly detection in distribution networks. ...
It leverages the spatio-temporal similarities amongst online monitoring data, and realizes anomaly detection by detecting the variations of the spatio-temporal correlation of the data. ...
arXiv:1810.08962v1
fatcat:sbdlyejevraxjincms6ihouavm
Total Variation Regularized Tensor RPCA for Background Subtraction From Compressive Measurements
2016
IEEE Transactions on Image Processing
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In this paper, we propose a novel tensor-based robust PCA (TenRPCA) approach for BSCM by decomposing video frames into backgrounds with spatial-temporal correlations and foregrounds with spatio-temporal ...
In this approach, we use 3D total variation (TV) to enhance the spatio-temporal continuity of foregrounds, and Tucker decomposition to model the spatio-temporal correlations of video background. ...
As shown in 3(b), we propose a multi-scale 3D total variation (TV) to describe the spatio-temporal smoothness. ...
doi:10.1109/tip.2016.2579262
pmid:27305675
fatcat:wtqbvueqonf5zih4dgswcdg7di
Challenges on Large Scale Surveillance Video Analysis
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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It is a very challenging but practical system, consists of multiple functionalities such as object detection, tracking, identification and behavior analysis. ...
All these tasks are based on our proposed online single camera multiple object tracking (MOT) system, which has been evaluated on the widely used MOT16 challenge benchmark. ...
interval and evaluate the spatio-temporal distance matrix. • Step 4: Combine the two distance matrices and perform the multi-camera multi-target matching following the Algorithm 2. ...
doi:10.1109/cvprw.2018.00017
dblp:conf/cvpr/FengJWCRG18
fatcat:k6rgabsprvdbzpzsnkkubee2mi
Spatio-temporal Based Approaches for Human Action Recognition in Static and Dynamic Background: a Survey
2016
Indian Journal of Science and Technology
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The objective of this review article is to study the spatio-temporal approaches for addressing the key issues such as multi-view, cluttering, jitter and occlusion in recognition of human action. ...
Relevant to multi-camera view, a negative space approach for identifying actions taken from different viewing angles was proposed. ...
The authors have presented the spatio-temporal Gaussian/Laplacian pyramids for multi-resolution video analysis. ...
doi:10.17485/ijst/2016/v9i5/72065
fatcat:5xxufjhhkrhh7gn26rt6qu3yfa
2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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Fu, Y., +, TIP 2020 6535-6548 Siamese Local and Global Networks for Robust Face Tracking. Qi, Y., +, Spatio-Temporal Multi-Scale Binary Descriptor. ...
., +, TIP 2020 3153-3167
Multi-Scale Multi-View Deep Feature Aggregation for Food Recognition.
Jiang, S., +, TIP 2020 265-276
Multi-Scale Temporal Cues Learning for Video Person Re-Identification. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
A Bayesian Framework for Multi-cue 3D Object Tracking
[chapter]
2004
Lecture Notes in Computer Science
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This paper presents a Bayesian framework for multi-cue 3D object tracking of deformable objects. ...
The proposed spatio-temporal object representation involves a set of distinct linear subspace models or Dynamic Point Distribution Models (DPDMs), which can deal with both continuous and discontinuous ...
Multi-cue object representation
Spatio-temporal shape representation Dynamic point distribution models capture object appearance by a set of linear subspace models with temporal transition probabilities ...
doi:10.1007/978-3-540-24673-2_20
fatcat:tnjhrellabfmppojpsgrw2xh7u
Towards Real-Time Systems for Vehicle Re-Identification, Multi-Camera Tracking, and Anomaly Detection
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Vehicle re-identification, multi-camera vehicle tracking, and anomaly detection are essential for city-scale intelligent transportation systems. ...
Scalability is critical for multi-camera systems, as the number of objects in a scene is not known a-priori. ...
regresses the start and end time of each anomaly through a spatio-temporal information matrix. ...
doi:10.1109/cvprw50498.2020.00319
dblp:conf/cvpr/PeriKRSRCC20
fatcat:xa6eqeyzizdf7cbeot6naq2hu4
Intelligent multi-camera video surveillance: A review
2013
Pattern Recognition Letters
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The covered topics include multi-camera calibration, computing the topology of camera networks, multi-camera tracking, object re-identification, multi-camera activity analysis and cooperative video surveillance ...
With the fast development of surveillance systems, the scales and complexities of camera networks are increasing and the monitored environments are becoming more and more complicated and crowded. ...
Chen et al. (2008) proposed an online unsupervised approach to learn both spatio-temporal and appearance relationships for a camera network. ...
doi:10.1016/j.patrec.2012.07.005
fatcat:vnbxmu55x5ditdmhjvsmloezr4
Spatio-temporal multi-scale motion descriptor from a spatially-constrained decomposition for online action recognition
2017
IET Computer Vision
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This work presents a spatio-temporal motion descriptor that is computed from a spatiallyconstrained decomposition and applied to online classification and recognition of human activities. ...
The method starts by computing a multi-scale dense optical flow that provides instantaneous velocity information for every pixel without explicit spatial regularization. ...
The spatio-temporal histograms are quantified for each detected RoI and for each of the defined subregions from the overlapped representation. ...
doi:10.1049/iet-cvi.2016.0055
fatcat:wtkj3efs5vgn5dxd2ttf6z7r74
Enhancing the Association in Multi-Object Tracking via Neighbor Graph
[article]
2020
arXiv
pre-print
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Most modern multi-object tracking (MOT) systems follow the tracking-by-detection paradigm. ...
To this end, we first utilize the spatio-temporal relations produced by the tracking self to efficiently select suitable neighbors for the targets. ...
For multi-object tracking, [15] and [23] adopt GNN to perform the data association. ...
arXiv:2007.00265v1
fatcat:wrvw6ktztvbfrdhncfimpwjlqi
Occlusion-Robust Online Multi-Object Visual Tracking using a GM-PHD Filter with CNN-Based Re-Identification
[article]
2021
arXiv
pre-print
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We use visual-spatio-temporal information obtained from object bounding boxes and deeply learned appearance representations to perform estimates-to-tracks data association for target labeling as well as ...
We propose a novel online multi-object visual tracker using a Gaussian mixture Probability Hypothesis Density (GM-PHD) filter and deep appearance learning. ...
with detections (in our case current filtered outputs or estimated states) for robust online multi-object tracking. ...
arXiv:1912.05949v6
fatcat:jrwnv2x63rg7rjxzv2hjs6y5li
Author Index
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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Global and Efficient Self-Similarity for Object Classification and Detection
What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes
Ferrie, Frank P. ...
Appearance Sharing: Recursive Compositional Models for Multi-View Multi-Object Detection SUN Database: Large Scale Scene Recognition from Abbey to Zoo Torresani, Lorenzo Simultaneous Point Matching and ...
doi:10.1109/cvpr.2010.5539913
fatcat:y6m5knstrzfyfin6jzusc42p54
2019 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 29
2019
IEEE transactions on circuits and systems for video technology (Print)
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., +, TCSVT Sept. 2019
2552-2566
KRMARO: Aerial Detection of Small-Size Ground Moving Objects Using
Kinematic Regularization and Matrix Rank Optimization. ...
., +, TCSVT Jan. 2019 263-274 Deep Continuous Conditional Random Fields With Asymmetric Inter-Object Constraints for Online Multi-Object Tracking. ...
doi:10.1109/tcsvt.2019.2959179
fatcat:2bdmsygnonfjnmnvmb72c63tja
Multi-stream CNN: Learning representations based on human-related regions for action recognition
2018
Pattern Recognition
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In addition, we select a secondary region that contains the major moving part of an actor based on motion saliency. ...
First, by improving foreground detection, the region of interest corresponding to the appearance and the motion of an actor can be detected robustly under realistic circumstances. ...
Not only some fine-scale moving objects would be removed, but also some large-scale moving objects in challenging conditions would be incorrectly captured. ...
doi:10.1016/j.patcog.2018.01.020
fatcat:ojy34is2vnfxpexoqi2utfh5l4
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