Reliable Multi-Object Tracking in the Presence of Unreliable Detections

Recent multi-object tracking (MOT) systems have leveraged highly accurate object detectors; however, training such detectors requires large amounts of labeled data. Although such data is widely available for humans and vehicles, it is significantly more scarce for other animal species. We present Robust Confidence Tracking (RCT), an algorithm designed to maintain robust performance even when detection quality is poor. In contrast to prior methods which discard detection confidence information, RCT takes a fundamentally different approach, relying on the exact detection confidence values to initialize tracks, extend tracks, and filter tracks. In particular, RCT is able to minimize identity switches by efficiently using low-confidence detections (along with a single object tracker) to keep continuous track of objects. To evaluate trackers in the presence of unreliable detections, we present a challenging real-world underwater fish tracking dataset, FISHTRAC. In an evaluation on FISHTRAC as well as the UA-DETRAC dataset, we find that RCT outperforms other algorithms when provided with imperfect detections, including state-of-the-art deep single and multi-object trackers as well as more classic approaches. Specifically, RCT has the best average HOTA across methods that successfully return results for all sequences, and has significantly less identity switches than other methods.Comment: The full journal version of this article (published in Pattern Recognition, Vol. 135) can be found at https://www.sciencedirect.com/science/article/pii/S0031320322005878. The article is open access. The source code and dataset can be found at https://github.com/tmandel/fish-detra

Importance of low-relief nursery habitat for reef fishes

Coastal restoration projects to mitigate environmental impacts have increased global demand for sand resources. Unfortunately, these resources are often extracted from sand/shell banks on the inner continental shelf, resulting in significant alteration or loss of low-relief reefs in coastal oceans. Experimental reefs (oyster shell, limestone rubble, composite) were deployed in the western Gulf of Mexico to assess their potential value as nurseries for newly settled reef fishes. Occurrence, abundance, and species richness of juvenile fishes were significantly higher on all three types of low-relief reefs compared with unconsolidated sediment. Moreover, reefs served as nursery habitat for a range of reef fish taxa (angelfishes, grunts, sea basses, snappers, and triggerfishes). Red snapper (Lutjanus campechanus) was the dominant species present on all experimental reefs (100% occurrence), and mean density of this species was markedly higher on each of the three low-relief reefs (\u3e40.0 individuals/reef) relative to comparable areas over unconsolidated sediment (0.2 individuals). Our results suggest creation or restoration of structurally complex habitat on the inner shelf has the potential to markedly increase early life survival and expedite the recovery of exploited reef fish populations, and therefore may represent a critical conservation tool for increasing recruitment and maintaining reef fish diversity