Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägern
State estimation of an unknown number of objects remains a challenging topic - despite the existence of theoretically bayes-optimal multi-object-filters - due to numerous assumptions in the modeling process. This thesis evaluates such filters in real multi-object-multi-sensor scenarios and proposes...
-д хадгалсан:
| Үндсэн зохиолч: | |
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| Формат: | Online |
| Хэл сонгох: | герман |
| Хэвлэсэн: |
KIT Scientific Publishing
2021
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| Нөхцлүүд: | |
| Онлайн хандалт: | 34501 |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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| Тойм: | State estimation of an unknown number of objects remains a challenging topic - despite the existence of theoretically bayes-optimal multi-object-filters - due to numerous assumptions in the modeling process. This thesis evaluates such filters in real multi-object-multi-sensor scenarios and proposes necessary extensions to existing models. The main application of the thesis is indoor pedestrian tracking. |
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