5 papers
GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms
Ãngel F. GarcÃa-Fernández, Jinhao Gu, Lennart Svensson +4
This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of the generalised optimal subpattern…
Occlusion-Aware Multi-Object Tracking via Expected Probability of Detection
Jan KrejÄÃ, Oliver Kost, Yuxuan Xia +2
This paper addresses multi-object systems, where objects may occlude one another relative to the sensor. The standard point-object model for detection-based sensors is enhanced so…
Deep Sequence-to-Sequence Models for GNSS Spoofing Detection
Jan Zelinka, Oliver Kost, Marek Hrúz
We present a data generation framework designed to simulate spoofing attacks and randomly place attack scenarios worldwide. We apply deep neural network-based models for spoofing d…
Model-based Multi-object Visual Tracking: Identification and Standard Model Limitations
Jan KrejÄÃ, Oliver Kost, Yuxuan Xia +2
This paper uses multi-object tracking methods known from the radar tracking community to address the problem of pedestrian tracking using 2D bounding box detections. The standard p…
TGOSPA Metric Parameters Selection and Evaluation for Visual Multi-object Tracking
Jan KrejÄÃ, Oliver Kost, OndÅej Straka +3
Multi-object tracking algorithms are deployed in various applications, each with different performance requirements. For example, track switches pose significant challenges for off…