PolyTrack: Tracking with Bounding Polygons
Not on the map. Why?
Abstract (arXiv)
In this paper, we present a novel method called PolyTrack for fast multi-object tracking and segmentation using bounding polygons. Polytrack detects objects by producing heatmaps of their center keypoint. For each of them, a rough segmentation is done by computing a bounding polygon over each instance instead of the traditional bounding box. Tracking is done by taking two consecutive frames as input and computing a center offset for each object detected in the first frame to predict its location in the second frame. A Kalman filter is also applied to reduce the number of ID switches. Since our target application is automated driving systems, we apply our method on urban environment videos. We trained and evaluated PolyTrack on the MOTS and KITTIMOTS datasets. Results show that tracking polygons can be a good alternative to bounding box and mask tracking. The code of PolyTrack is available at https://github.com/gafaua/PolyTrack.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 24 of its 31 references that are in the map. First posted on arXiv 2 Nov 2021.
Builds on
24 of 31 references.
References · 24
- 2014Microsoft COCO: Common Objects in Contextcited by 17,498
- 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
- 2017Mask R-CNNcited by 7,259
- 2017Simple Online and Realtime Tracking with a Deep Association Metriccited by 908
- 2016Simple Online and Realtime Trackingcited by 862
- 2020HOTA: A Higher Order Metric for Evaluating Multi-Object Trackingcited by 546
- 2020Tracking Objects as Pointscited by 483
- 2019Tracking without bells and whistlescited by 382
- 2019MOTS: Multi-Object Tracking and Segmentationcited by 222
- 2020ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentationcited by 95
- 2021EagerMOT: 3D Multi-Object Tracking via Sensor Fusioncited by 83
- 2016Learning by tracking: Siamese CNN for robust target associationcited by 79
12 more
- 2019Spatial-Temporal Relation Networks for Multi-Object Trackingcited by 74
- 2021Do Different Tracking Tasks Require Different Appearance Models?cited by 62
- 2019Track to Reconstruct and Reconstruct to Trackcited by 49
- 2017Deep Network Flow for Multi-Object Trackingcited by 45
- 2018Beyond Pixels: Leveraging Geometry and Shape Cues for Online Multi-Object Trackingcited by 40
- 2020Segment as Points for Efficient Online Multi-Object Tracking and Segmentationcited by 36
- 2017Accurate Single Stage Detector Using Recurrent Rolling Convolutioncited by 27
- 2020ReMOTS: Self-Supervised Refining Multi-Object Tracking and Segmentationcited by 17
- 2021CenterPoly: real-time instance segmentation using bounding polygonscited by 6
- 2018Tracking Multiple Moving Objects Using Unscented Kalman Filtering Techniquescited by 2
- 2018Multiple Object Tracking in Urban Traffic Scenes with a Multiclass Object Detectorcited by 1
- 2020Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusioncited by 1
Built on by
Not cited yet.