Better object detection by combining scores of multiple detectors using probability with DBF
Better object detection by combining scores of multiple detectors using probability with DBF
DBF: Dynamic Belief Fusion for Combining Multiple Object Detectors
arXiv paper abstract https://arxiv.org/abs/2204.02890v1
arXiv PDF paper https://arxiv.org/pdf/2204.02890v1.pdf
... propose ... fusion approach called dynamic belief fusion (DBF) that ... integrates ... scores of ... detections from multiple object detection methods.
... ambiguity in each detection score is estimated using a confidence model built on a precision-recall relationship of the ... detector.
For each detector ... DBF ... calculates the probabilities of three hypotheses (target, non-target, and intermediate state ...) ... on the confidence level of the detection score conditioned on the prior confidence model of individual detectors
... probability distributions over three hypotheses of all the detectors are optimally fused via the Dempster's combination rule.
... show that the detection accuracy of the DBF is significantly higher than any of the baseline fusion approaches as well as individual detectors ...
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