![]() Several patches based on OSPA have been put forward as well, such as Hellinger-OSPA, which concerned the uncertainty, Q-OSPA, which add a quality factor to OSPA, Multi-Group OSPA for hierarchical finite sets, and IoU-OSPA, which adapted for the bounding boxes in vision tasks. On this basis, Generalized OSPA (GOSPA) and Complete OSPA (COSPA) was proposed to avoid the “spooky effect” in optimal OSPA estimation and completed it. Proposed by, OSPA balanced the difference of cardinalities by bring “dummy” point into finite sets, then bounded the penalty of cardinality as a consequence, it is more intuitive than the former ones. However, simply by normalizing the unbalanced cardinalities to construct a distribution leads to counterintuitive results sometimes with the OMAT metric. Due to the insensitivity to differences in cardinalities of finite sets and overreaction to outliers with the Hausdorff distance, the optimal mass transfer (OMAT) metric was proposed in, bases on the Wasserstein distance between the distributions of finite sets. The Hausdorff distance on finite sets is the first metric applied in MTT. Considering the indispensable importance of metrics’ mathematically consistency in performance evaluation, pointed out in, here we focus on metrics and briefly review several widely used ones in MTT. Both metrics and non-metrics have been discussed. The performance evaluation of MTT is a long-standing problem across many topics. ![]() Relying on the metric space derived from the definition of metric on a space of finite sets, one can rigorously analyze the convergency of estimators, or do a nearest neighbor search, cluster and classify on finite sets. Metrics for finite sets has potential applications in multisensor-multitarget sensor field of view (FOV) management, since its many-to-many consistency in optimizing. ![]() Metrics can also be considered as a criterion to obtain estimators from the posterior probability density of random finite sets, for example, minimizing the mean optimal subpattern assignment (OSPA). Metrics can give a mathematically consistent miss-distance between estimates and the ground truth to evaluate algorithm performance. In the problem of MTT, a well-defined metric is significant in following aspects: (1) Performance evaluation. The concept of the metric herein stands for a distance function on finite sets, which satisfies non-negativity, symmetry, identity of indiscernibles and triangle inequality in a mathematical sense. Just like the metrics on vectors such as Euclidean distance and Mahalanobis distance, which represent the meaning of the miss-distance between two states of object in single-target tracking, a definition of metric between two finite sets is also of importance in multi-target state tracking. Multi-target tracking (MTT) with multiple heterogeneous sensors has a wide range of applications in the fields of autonomous driving, surveillance in maritime and aerial space, and so on. The proposed label metric is a mathematic metric, and its advantages are illustrated by examples in several cases. A Wasserstein distance type metric then can be defined among the distribution represented by any two labels. The hierarchical multi-level class label is introduced as an attached label to finite sets based on the hierarchical tree-structured categorization. This paper proposed a hierarchical multi-level class label for multi-class multi-target tracking under hierarchical multilevel classification, which can synthetically measure the state errors, cardinality error, and mis-classification. Considering its performance evaluation, the traditional optimal subpattern assignment (OSPA) method tends to calculate a separate metric for each class of targets, or introduce other indexes such as the classification error rate, which decreases the value of OSPA as a comprehensive single metric. $scope.Aiming at multiple quantities and types of targets, multi-class multi-target tracking usually faces not only cardinality errors, but also mis-classification problems. If ($scope.wootMessages != undefined) manual click or auto - click/null When you reply, it will also be translated back to lilicon-trans-text.".replace(/lilicon-trans-text/g, tr_obj.title) ![]() Tr_text = "This post originally written in lilicon-trans-text has been computer translated for you. Script.src = "" + data_account + "/" + data_palyer + "_default/" Var script = document.createElement('script') Var data = div.getElementsB圜lassName("video-js") ![]()
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