Multiple Object Tracking from appearance by hierarchically clustering tracklets
Current approaches in Multiple Object Tracking (MOT) rely on the spatio-temporal coherence between detections combined with object appearance to match objects from consecutive frames. In this work, we explore MOT using object appearances as the main source of association between objects in a video, using spatial and temporal priors as weighting factors. We form initial tracklets by leveraging on the idea that instances of an object that are close in time should be similar in appearance, and build the final object tracks by fusing the tracklets in a hierarchical fashion. We conduct extensive experiments that show the effectiveness of our method over three different MOT benchmarks, MOT17, MOT20, and DanceTrack, being competitive in MOT17 and MOT20 and establishing state-of-the-art results in DanceTrack.
Code (1)
Tasks
ClusteringMulti-Object TrackingMultiple Object TrackingObjectObject TrackingSimilar Papers 제목 키워드 기반
Hierarchical Convolutional Features for Visual Tracking
Visual object tracking is challenging as target objects often undergo significant appearance changes caused by deformation, abrupt motion, background clutter and occlusion. In this paper, we exploit features extracted fr…
Object RecognitionObject TrackingVisual Object TrackingVisual TrackingUnsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowledge or supervision to associate data corr…
ClusteringMultiple Object TrackingObject TrackingTackling multiple object tracking with complicated motions—Re-designing the integration of motion and appearance
Although numerous data association methods have been proposed for Multiple Object Tracking (MOT), how to integrate different features in the data association remains an open problem. For instance, over-relying on the mot…
Multiple Object TrackingObjectObject TrackingMulti-tracklet Tracking for Generic Targets with Adaptive Detection Clustering
Tracking specific targets, such as pedestrians and vehicles, has been the focus of recent vision-based multitarget tracking studies. However, in some real-world scenarios, unseen categories often challenge existing metho…
Multiple Object TrackingExtending Multi-Object Tracking systems to better exploit appearance and 3D information
Tracking multiple objects in real time is essential for a variety of real-world applications, with self-driving industry being at the foremost. This work involves exploiting temporally varying appearance and motion infor…
Multi-Object TrackingObjectObject TrackingReal-Time Multi-Object Tracking