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A camera-based system for tracking people in real time
1996
Proceedings of 13th International Conference on Pattern Recognition
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This paper describes a s y s t e m f o r real-time tracking of people in video sequences. ...
It identijies feature points in each video f r a m e , matches feature points across f r a m e s t o produce feature ')aths", t h e n groups short-lived and partially overlapping feature paths i n t o ...
The system has been tested on several video sequences of people traffic in different indoor environments. ...
doi:10.1109/icpr.1996.546795
dblp:conf/icpr/Segen96
fatcat:vvi73h6ulbhorohd5imcgkqexm
Automatically Determining Dominant Motions in Crowded Scenes by Clustering Partial Feature Trajectories
2007
2007 First ACM/IEEE International Conference on Distributed Smart Cameras
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Results on real video sequences demonstrate that the approach can successfully identify both dominant and anomalous motions in crowded scenes. ...
Our approach begins by independently tracking low-level features using optical flow. ...
However, results on real video sequences demonstrate that the proposed clustering algorithm can identify both dominant and anomalous motions in crowded scenes by clustering these partial feature trajectories ...
doi:10.1109/icdsc.2007.4357505
dblp:conf/icdsc/CheriyadatR07
fatcat:d42vxyl6uvazpkj4wblvn7orxy
Detecting global motion patterns in complex videos
2008
Pattern Recognition (ICPR), Proceedings of the International Conference on
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In this paper, we propose an algorithm that uses instantaneous motion field of the video instead of long-term motion tracks for learning the motion patterns. ...
We also use the super tracks for eventbased video matching. The efficacy of the approach is demonstrated on challenging real-world sequences. ...
Acknowledgements: This research was funded by the US Government VACE program. ...
doi:10.1109/icpr.2008.4760950
dblp:conf/icpr/HuAS08
fatcat:uhcxw3i3krdxdpuah4wzoy32dq
A Novel Trajectory Clustering Approach for Motion Segmentation
[chapter]
2010
Lecture Notes in Computer Science
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We propose a novel clustering scheme for spatio-temporal segmentation of sparse motion fields obtained from feature tracking. ...
Results show, that our method successfully segments the motion components even in particularly noisy sequences. ...
[1] [2] [3] ) we extract motion trajectories by feature tracking directly from the raw video sequence and omit object segmentation. ...
doi:10.1007/978-3-642-11301-7_44
fatcat:ergaccp2tndrbilyti6lwxec6m
Using dynamic Bayesian network for scene modeling and anomaly detection
2009
Signal, Image and Video Processing
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In this paper, we address the problem of scene modeling for performing video surveillance. ...
During the training phase, the input trajectories are used to identify different paths or routes commonly taken by the objects in a scene. ...
[9] demonstrate the use of network tomography for statistical tracking of activities in a video sequence. ...
doi:10.1007/s11760-008-0099-7
fatcat:4522ilppcza5ja6t7b3a5apyhu
Learning Pedestrian Trajectories with Kernels
2010
2010 20th International Conference on Pattern Recognition
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We demonstrate the effectiveness of our method incorporating the learned motion model into a multiperson tracking algorithm and testing it on several video surveillance sequences. ...
To model crossing paths we rely on a clustering algorithm based on Kernel K-means with a Dynamic Time Warping (DTW) kernel. ...
Typical paths in our scenario.
Figure 2 . 2 (a) Clustered trajectories. (b) Paths extracted tracking with (red) and without (blue) the learned motion model
.a. ...
doi:10.1109/icpr.2010.45
dblp:conf/icpr/RicciTZ10
fatcat:m2sbqx5egzgq3lhyqdnjdzrfhu
Multi feature path modeling for video surveillance
2004
Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.
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Finally, the curvature features capture discontinuities in velocity, acceleration, and position of the trajectory. We use real-world pedestrian sequences to demonstrate the practicality of our method. ...
An envelope boundary and an average trajectory are computed for each path. During the testing phase we use three features for trajectory matching in a hierarchical fashion. ...
An example of an unusual behavior might be a person walking in a region not used by most people, a car following a zigzag path, or a person running in a region where most people simply walk. ...
doi:10.1109/icpr.2004.1334359
dblp:conf/icpr/JunejoJS04
fatcat:ffsetzkc5zhc5fzbqv7fvr3voy
Spatio-temporal Discovery: Appearance + Behavior = Agent
[chapter]
2006
Lecture Notes in Computer Science
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Improved algorithms for video segmentation and tracking under occlusion enable us to construct models that characterize agents in terms of motion and interaction with other objects. ...
Using uncalibrated camera images, we characterize objects discovered in the scene by their shape and motion attributes, and cluster these using agglomerative hierarchical clustering. ...
In this work, we consider dynamic image sequences and use improved algorithms for video segmentation and tracking under occlusion to construct coherent motion histories and occlusion relations simulating ...
doi:10.1007/11949619_46
fatcat:dqkvsh4g5nb6rhrkhaouwpm54i
Toward Abnormal Trajectory and Event Detection in Video Surveillance
2017
IEEE transactions on circuits and systems for video technology (Print)
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In this paper we present a unified approach for abnormal behavior detection and group behavior analysis in video scenes. ...
threats for cargo video surveillance [3] . ...
After the clustering step, a tree is build with the sequence of clusters, and an anomalous trajectory is defined as a trajectory that matches a path in the tree of clusters with low probability. ...
doi:10.1109/tcsvt.2016.2589859
fatcat:rrp3f42tzzdbpipky4r54kzupu
Multi-Person Tracking by Multicut and Deep Matching
[article]
2016
arXiv
pre-print
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In [1], we proposed a graph-based formulation that links and clusters person hypotheses over time by solving a minimum cost subgraph multicut problem. ...
In this paper, we modify and extend [1] in three ways: 1) We introduce a novel local pairwise feature based on local appearance matching that is robust to partial occlusion and camera motion. 2) We perform ...
boxes that possibly identify people in a video sequence. ...
arXiv:1608.05404v1
fatcat:3msnj777abfnveshtpwm5uoqmy
Multi-person Tracking by Multicut and Deep Matching
[chapter]
2016
Lecture Notes in Computer Science
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In Tang et al. (2015) , we proposed a graph-based formulation that links and clusters person hypotheses over time by solving a minimum cost subgraph multicut problem. ...
In this paper, we modify and extend Tang et al. (2015) in three ways: (1) We introduce a novel local pairwise feature based on local appearance matching that is robust to partial occlusion and camera motion ...
This work has been supported by the Max Planck Center for Visual Computing and Communication. ...
doi:10.1007/978-3-319-48881-3_8
fatcat:bpcnvnemqnbzjhkoyihhrn5j5m
Clustering Motion for Real-Time Optical Flow Based Tracking
2012
2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance
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Good Features to Track, select points to be tracked based on appearance features such as cornerness and therefore neglecting the motion exhibited by the selected points. ...
The number of trajectories assigned to each motion cluster is adapted by initializing and removing tracked points by means of feed-back. ...
Optical flow is increasingly being used in video surveillance systems, e.g., in order to distinguish people by motion in crowds, for crowd analysis and activity monitoring. ...
doi:10.1109/avss.2012.20
dblp:conf/avss/SenstEKS12
fatcat:dcauwtuvejaujopnyetr7nevae
Instantly indexed multimedia databases of real world events
2002
IEEE transactions on multimedia
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This system analyzes video from multiple cameras in real time and captures the activity of the players and the ball in the form of motion trajectories. ...
Index Terms-Broadcast, content-based retrieval, Internet, television, tracking, video, vision, visual data mining, visualization. 1520-9210/02$17.00 © 2002 IEEE ...
A feature path consists of a sequence of feature matches and indicates the motion of a feature over time. ...
doi:10.1109/tmm.2002.1017739
fatcat:676g7lxydndgldziaisfmlzvtm
Moving Pixels in Static Cameras: Detecting Dangerous Situations due to Environment or People
[chapter]
2010
Studies in Computational Intelligence
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The second refers to the problem of detecting suspicious or abnormal people behaviors by means of people trajectory analysis in a multiple cameras video-surveillance scenario. ...
image features, such as color information and texture energy computed by the means of the Wavelet transform. ...
First, after the clustering, clusters cardinality naturally represents by definition how often a specific path occurs, thus allowing to classify the paths in abnormal (unfrequent) and normal (frequent) ...
doi:10.1007/978-3-642-11756-5_1
fatcat:rhlbtuv26nbifbndgc6z3qo64e
Crowded Scene Analysis: A Survey
2015
IEEE transactions on circuits and systems for video technology (Print)
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2015 pre-print arXiv:1502.01812v1 fatcat:frsqmw6dgjgajln7eojve7bnjy
In the past few years, an increasing number of works on crowded scene analysis have been reported, covering different aspects including crowd motion pattern learning, crowd behavior and activity analysis ...
We first provide the background knowledge and the available features related to crowded scenes. ...
Tracklets are collected by tracking dense feature points from the video of crowded scenes, and motion patterns are then learned by clustering the tracklets. In Jodoin et al. ...
doi:10.1109/tcsvt.2014.2358029
fatcat:prgoh37gjfcl7n6dp2u6tsdoda
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