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Motion segmentation by a model-based clustering approach of incomplete trajectories
Published on Nov 30, 20112826 Views
In this paper, we present a framework for visual object tracking based on clustering trajectories of image key points extracted from a video. The main contribution of our method is that the trajectori
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Chapter list
Motion segmentation by model-based clustering of incomplete trajectories00:00
Outline - 100:18
Problem Explanation00:40
State of the art01:13
Method Overview02:11
The Proposed Method02:42
Outline - 203:36
Key Points03:40
Trajectories Creation04:06
Extracting Trajectories05:37
Outline - 306:01
Input Trajectories06:09
Linear Regression Model06:31
Kernel matrix07:26
Translation term08:15
Conditional density of observations08:57
Regression Mixture Model09:39
Sparse Modeling10:41
MAP estimation problem11:34
EM Algorithm - 111:56
EM Algorithm - 212:23
EM Algorithm - 312:31
Extracted knowledge (output)13:03
Initialization Strategy - 113:54
Initialization Strategy - 214:42
Outline - 415:00
Experimental Results15:03
Experiments with simulated data sets - 115:21
Experiments with simulated data sets - 215:31
ecmlpkdd2011_karavasilis_trajectories_01_Page_3115:41
Experiments with simulated data sets - 415:55
Experiments with simulated data sets - 516:06
Experiments with real data sets - 116:18
Experiments with real data sets - 216:25
Experiments with real data sets - 316:35
Experiments with real data sets - 416:44
Experiments with real data sets - 516:53
Experiments with real data sets - 617:13
Outline - 417:16
Conclusions17:16
Thank you17:45