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Stixmentation - Probabilistic Stixel based Traffic Scene Labeling
Published on Oct 09, 20123885 Views
The detection of moving objects like vehicles, pedestrians or bicycles from a mobile platform is one of the most challenging and most important tasks for driver assistance and safety systems. For th
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Chapter list
Stixmentation – Probabilistic Stixel based Traffic Scene Labeling00:00
Roadmap: Detecting Moving Objects00:28
Stereo Computation - 101:16
Stereo Computation - 201:44
Stixel Computation - 102:17
Stixel Computation - 202:42
Stixel Motion Estimation - 102:55
Stixel Motion Estimation - 203:22
1st Try: Simple Velocity Thresholding - 103:44
1st Try: Simple Velocity Thresholding - 204:22
Related Work (1)04:36
Related Work (2)05:11
Better Try: Probabilistic Formulation - 106:55
Better Try: Probabilistic Formulation - 207:33
Better Try: Probabilistic Formulation - 307:42
Better Try: Probabilistic Formulation - 407:54
Data Term: Prior Term - 108:00
Data Term: Prior Term - 208:36
A priori knowledge - 108:56
A priori knowledge - 209:31
Data Term: Height Feature - 110:04
Data Term: Height Feature - 210:20
Data Term: Height Feature - 310:39
Data Term: Height Feature - 410:49
Data Term: Height Feature - 510:57
Data Term: Position Feature - 111:13
Data Term: Position Feature - 211:16
Data Term: Position Feature - 311:20
Data Term: Position Feature - 411:29
Data Term: Position Feature - 512:03
Data Term: Position Feature - 612:09
Data Term: Position Feature - 712:11
Data Term: Position Feature - 812:13
Data Term: Velocity Feature - 112:27
Data Term: Velocity Feature - 212:38
Data Term: Velocity Feature - 312:47
Data Term: Velocity Feature - 413:23
Data Term: Velocity Feature - 513:31
Data Term: Velocity Feature - 613:37
Experimental Results13:46
Experimental Results: Example14:27
Conclusion15:25