Abstract:
The track coalescence effect degrades the performance of probabilistic data association trackers in dense target scenarios. Recently, it has been observed that an opposit...Show MoreMetadata
Abstract:
The track coalescence effect degrades the performance of probabilistic data association trackers in dense target scenarios. Recently, it has been observed that an opposite effect exists with trackers that utilize hard data association, which we denote as the track repulsion effect. In this paper, we examine this effect in the context of a crossing target scenario, and explore the effectiveness of a track-oriented multi-hypothesis tracker in combating this effect, with both single-stage and multi-stage processing configurations.
Published in: 2009 12th International Conference on Information Fusion
Date of Conference: 06-09 July 2009
Date Added to IEEE Xplore: 18 August 2009
Print ISBN:978-0-9824-4380-4
Conference Location: Seattle, WA, USA
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Tracking Performance ,
- Multistage Process ,
- Computation Time ,
- Simple Example ,
- Performance Benefits ,
- Computationally Intractable ,
- Data Fusion ,
- Number Of Hypotheses ,
- Value In Stage ,
- Undersea ,
- Critical Angle ,
- Number Of Tracks ,
- Tracking Approach ,
- Real-time Surveillance ,
- Primary Sensor ,
- Optimal Tracking ,
- Global Hypothesis ,
- Multi-feature Fusion ,
- Maximum Likelihood Solution ,
- Optimal Fusion
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Tracking Performance ,
- Multistage Process ,
- Computation Time ,
- Simple Example ,
- Performance Benefits ,
- Computationally Intractable ,
- Data Fusion ,
- Number Of Hypotheses ,
- Value In Stage ,
- Undersea ,
- Critical Angle ,
- Number Of Tracks ,
- Tracking Approach ,
- Real-time Surveillance ,
- Primary Sensor ,
- Optimal Tracking ,
- Global Hypothesis ,
- Multi-feature Fusion ,
- Maximum Likelihood Solution ,
- Optimal Fusion
- Author Keywords