Vancura, Daniel (2012)
Hypothesis Generation with Part Detectors for Multi-Target Tracking.
Technische Universität Darmstadt
Bachelorarbeit, Bibliographie
Kurzbeschreibung (Abstract)
Tracking people in occluded scenes is a hard problem and different approaches exist to offer more robustness against the effect of insufficient detections and clutter in retrieved positions. This thesis is about avoiding these drawbacks of missing hypotheses by using multiple detection categories for human tracking. Used for tracking is a system, that uses energy minimization techniques. The common approach for tracking is to use bounding boxes of full person detections only. The remaining problem with this approach is that partially occluded persons often cannot be detected when using a simple Histogram of Oriented Gradients (HOG) detector with a Support Vector Machine (SVM) for classification. To detect partially occluded pedestrians nonetheless, additional detectors can be run to detect only parts of persons that may appear in occluded scenes and enhance the tracking results. In this thesis the main steps and results of this approach will be evaluated and compared to existing approaches.
| Typ des Eintrags: | Bachelorarbeit |
|---|---|
| Erschienen: | 2012 |
| Autor(en): | Vancura, Daniel |
| Art des Eintrags: | Bibliographie |
| Titel: | Hypothesis Generation with Part Detectors for Multi-Target Tracking |
| Sprache: | Englisch |
| Publikationsjahr: | 2012 |
| Kurzbeschreibung (Abstract): | Tracking people in occluded scenes is a hard problem and different approaches exist to offer more robustness against the effect of insufficient detections and clutter in retrieved positions. This thesis is about avoiding these drawbacks of missing hypotheses by using multiple detection categories for human tracking. Used for tracking is a system, that uses energy minimization techniques. The common approach for tracking is to use bounding boxes of full person detections only. The remaining problem with this approach is that partially occluded persons often cannot be detected when using a simple Histogram of Oriented Gradients (HOG) detector with a Support Vector Machine (SVM) for classification. To detect partially occluded pedestrians nonetheless, additional detectors can be run to detect only parts of persons that may appear in occluded scenes and enhance the tracking results. In this thesis the main steps and results of this approach will be evaluated and compared to existing approaches. |
| Freie Schlagworte: | Computer vision, Computer vision based tracking, Occlusion models, People detection, People tracking, Tracking |
| Zusätzliche Informationen: | 42 p. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 12 Nov 2018 11:16 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum