A generalized labeled multi-bernoulli filter with object spawning
Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter, such as the generalized labeled multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide v...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
IEEE
2018
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| Online Access: | http://purl.org/au-research/grants/arc/DP170104854 http://hdl.handle.net/20.500.11937/72442 |
| Summary: | Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter, such as the generalized labeled multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide variety of applications, it lacks the capability to capture spawned tracks and their lineages. In this paper, we propose a new Generalized Labeled Multi-Bernoulli (GLMB)-based filter that formally incorporates spawning, in addition to birth. This formulation enables the joint estimation of a spawned object's state and information regarding its lineage. Simulations results demonstrate the efficacy of the proposed formulation. |
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