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- W2098061282 abstract "A novel approach to utilizing negative information to improve the accuracy of extended multi-object tracking is presented. The parameterized probability density of object tracks unresolved in sensor data is updated via inferences about the sensor-to-object geometries necessary to result in occlusion of the unresolved object. Negative information is also leveraged to improve data association and to enable a novel death model, all of which contribute to a more accurate and precise belief of the local scene. Simulation and experimental results are presented from a common autonomous driving scenario." @default.
- W2098061282 created "2016-06-24" @default.
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- W2098061282 date "2013-05-01" @default.
- W2098061282 modified "2023-09-24" @default.
- W2098061282 title "Modeling and fusing negative information for dynamic extended multi-object tracking" @default.
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- W2098061282 doi "https://doi.org/10.1109/icra.2013.6631019" @default.
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