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Center-based 3D Object Detection and Tracking [article]

Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl
2021 arXiv   pre-print
In this paper, we instead propose to represent, detect, and track 3D objects as points.  ...  Our framework, CenterPoint, first detects centers of objects using a keypoint detector and regresses to other attributes, including 3D size, 3D orientation, and velocity.  ...  Conclusion We proposed a center-based framework for simultaneous 3D object detection and tracking from the Lidar point cloud.  ... 
arXiv:2006.11275v2 fatcat:xqq74fqgpvhudfbqunuf7zp6t4

Center-based 3D Object Detection and Tracking

Tianwei Yin, Xingyi Zhou, Philipp Krähenbühl
2020
In this paper, we instead propose to represent, detect, and track 3D objects as points.  ...  Our framework, CenterPoint, first detects centers of objects using a keypoint detector and regresses to other attributes, including 3D size, 3D orientation, and velocity.  ...  Conclusion We proposed a center-based framework for simultaneous 3D object detection and tracking from the Lidar point-clouds.  ... 
doi:10.48550/arxiv.2006.11275 fatcat:u5zpdmk5jzeslanrk47tzps3sa

1st Place Solutions for Waymo Open Dataset Challenges – 2D and 3D Tracking [article]

Yu Wang, Sijia Chen, Li Huang, Runzhou Ge, Yihan Hu, Zhuangzhuang Ding, Jie Liao
2020 arXiv   pre-print
An efficient and pragmatic online tracking-by-detection framework named HorizonMOT is proposed for camera-based 2D tracking in the image space and LiDAR-based 3D tracking in the 3D world space.  ...  This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D tracking challenges.  ...  There are a group of pragmatic tracking-by-detection approaches for 2D/3D multiple object tracking whose data association method is simply based on bounding box overlap or object center distance and built  ... 
arXiv:2006.15506v1 fatcat:jbyo6xd2ovepxaeq54e2fm6fie

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving [article]

Chenxu Luo, Xiaodong Yang, Alan Yuille
2021 arXiv   pre-print
SimTrack integrates the tracked object association, newborn object detection, and dead track killing in a single unified model.  ...  3D multi-object tracking in LiDAR point clouds is a key ingredient for self-driving vehicles.  ...  Preliminary Our approach exploits the center based representation for 3D objects.  ... 
arXiv:2108.10312v1 fatcat:42bt4mpumvfxhnvscfm5azykru

Monocular Quasi-Dense 3D Object Tracking [article]

Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer, Trevor Darrell, Fisher Yu, Min Sun
2021 arXiv   pre-print
On the Waymo Open benchmark, we establish the first camera-only baseline in the 3D tracking and 3D detection challenges.  ...  A reliable and accurate 3D tracking framework is essential for predicting future locations of surrounding objects and planning the observer's actions in numerous applications such as autonomous driving  ...  [56] combining 3D LiDAR detection with the center-based association paradigm from CenterTrack [57] to perform joint 3D detection and tracking.  ... 
arXiv:2103.07351v1 fatcat:tn7il5h4gbcrxdl5kvb7otgzcu

CFTrack: Center-based Radar and Camera Fusion for 3D Multi-Object Tracking [article]

Ramin Nabati, Landon Harris, Hairong Qi
2021 arXiv   pre-print
Our proposed method uses a center-based radar-camera fusion algorithm for object detection and utilizes a greedy algorithm for object association.  ...  In this work, we propose an end-to-end network for joint object detection and tracking based on radar and camera sensor fusion.  ...  B. 3D Multi-Object Tracking Hu et al. [28] combine 2D image-based feature association and 3D LSTM-based motion estimation for 3D object tracking.  ... 
arXiv:2107.05150v1 fatcat:xdrb2npzyrayjk3y4fw44vg3gu

Joint Monocular 3D Vehicle Detection and Tracking [article]

Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu
2019 arXiv   pre-print
In this paper, we propose a novel online framework for 3D vehicle detection and tracking from monocular videos.  ...  Our experiments on simulation, KITTI, and Argoverse datasets show that our 3D tracking pipeline offers robust data association and tracking.  ...  Acknowledgements The authors gratefully acknowledge the support of Berkeley AI Research, Berkeley DeepDrive and MOST-107 2634-F-007-007, MOST Joint Research Center for AI Technology and All Vista Healthcare  ... 
arXiv:1811.10742v3 fatcat:jwsqawtuyvdxvfxewe34kgbx4q

A New Framework of Moving Object Tracking based on Object Detection-Tracking with Removal of Moving Features

Ly Quoc Ngoc, Nguyen Thanh, Le Bao
2020 International Journal of Advanced Computer Science and Applications  
Third, proposed tracking system based on integration of single tracker as Deep Particle Filter and Object Detection as Yolov3.  ...  First, the proposed Unified Visual based-MOT system can do the tasks such as Localization, 3D Environment Reconstruction and Tracking based on Stereo Camera and Inertial Measurement Unit (IMU).  ...  Accuracy of the Tracked Object Center in 3D Object center is estimated as the average of all 3D points of the object being considered.  ... 
doi:10.14569/ijacsa.2020.0110406 fatcat:kclpyzrn6bbxlny2h76tosfoxe

Driving Behavior-aware Network for 3D Object Tracking in Complex Traffic Scenes

Qingnan Li, Ruimin Hu, Zhongyuan Wang, Zhi Ding
2021 IEEE Access  
We use Deep Layer Aggregation (DLA) [32] as network backbone, and create convolutional heads of object center point, 2D and 3D bounding box size, depth, and orientation for 3D object detection.  ...  Based on this natural formulation, instead of encoding object center offsets on 2D plane for 3D tracking [3] , we take full advantage of spatialtemporal details across consecutive frames and propose an  ...  He is currently an Associate Professor with the Engineering Research Center for Transportation Systems, Wuhan University of Technology.  ... 
doi:10.1109/access.2021.3068899 fatcat:o6yld5drsjhwnf7yszyjagw7ta

Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery

Xiaofei Du, Maximilian Allan, Alessio Dore, Sebastien Ourselin, David Hawkes, John D. Kelly, Danail Stoyanov
2016 International Journal of Computer Assisted Radiology and Surgery  
In both cases, we show an improvement over using 3D tracking alone suggesting that combining 2D and 3D tracking is a promising solution to challenges in surgical instrument tracking.  ...  However, vision-based methods suffer from drift, and in the case of occlusions, shadows and fast motion, they can be subject to complete tracking Electronic supplementary material The online version of  ...  Acknowledgments We would like to acknowledge Simon Di Maio and Intuitive Surgical Inc., CA, for their support and input to this work.  ... 
doi:10.1007/s11548-016-1393-4 pmid:27038963 pmcid:PMC4893384 fatcat:wn2feqvsk5h4ffpd3cyp2hy4qm

Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras [article]

Zhengxia Zou, Rusheng Zhang, Shengyin Shen, Gaurav Pandey, Punarjay Chakravarty, Armin Parchami, Henry X. Liu
2022 arXiv   pre-print
The proposed framework covers a full-stack of roadside perception pipeline for infrastructure-assisted autonomous driving, including object detection, object localization, object tracking, and multi-camera  ...  Unlike previous vision-based perception frameworks rely upon depth offset or 3D annotation at training, we adopt a modular decoupling design and introduce a landmark-based 3D localization method, where  ...  Some representative approaches includes Faster R-CNN [10] , [11] , [12] , SSD [13] , and YOLO [14] , [15] , [16] for object detection; DeepSort [17] and Center Track [18] for object tracking  ... 
arXiv:2206.09770v1 fatcat:nr4tbimp4rgg5lntolkv2wxyda

Tracking Objects as Points [article]

Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl
2020 arXiv   pre-print
Nowadays, tracking is dominated by pipelines that perform object detection followed by temporal association, also known as tracking-by-detection.  ...  CenterTrack is easily extended to monocular 3D tracking by regressing additional 3D attributes.  ...  The tracker can simply learn to keep those detections from the prior frame around. 3D object detection and tracking. 3D trackers replace the object detection component in standard tracking systems with  ... 
arXiv:2004.01177v2 fatcat:7nv6ylcf7rfgpfzspdiddp2vzi

Stereo and Motion Based 3D High Density Object Tracking [chapter]

Junli Tao, Benjamin Risse, Xiaoyi Jiang
2014 Lecture Notes in Computer Science  
These metrics are used to analyse the effect of detection noise and compare our tracking algorithm with two state-of-the-art 3D tracking methods based on simulated data with hundreds of flies.  ...  In this paper we propose a high density object tracking algorithm.  ...  IDS is reduced significantly due to temporal tracking information. Similar to the detection-based ground truth MT and Acc increase with the number of objects.  ... 
doi:10.1007/978-3-642-53842-1_12 fatcat:oglitdkbvnh4fow56oqjmvwziy

Hybrid model and appearance based eye tracking with kinect

Kang Wang, Qiang Ji
2016 Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications - ETRA '16  
We further propose to utilize appearance information to help the basic model based methods. Appearance information can help better detection of gaze related features (Eg, pupil center).  ...  Specifically, unlike traditional 3D model based methods which rely on cornea reflections, we plan to retrieve 3D information from depth sensor (Eg, Kinect).  ...  Plans for future work We have already built the basic model based gaze tracking system.  ... 
doi:10.1145/2857491.2888591 dblp:conf/etra/WangJ16 fatcat:bwlph4kbvbf7njzkkgf7h2afpm

Robust 3D Detection in Traffic Scenario with Tracking-Based Coupling System [chapter]

Zhuoli Zhou, Shitao Chen, Rongyao Huang, Nanning Zheng
2020 IFIP Advances in Information and Communication Technology  
In this paper, we propose a coupling system which combines 3D object detection and multi-object tracking into one framework.  ...  We use the tracked objects as a reference in 3D object detection, in order to locate objects, reduce false or missing alarms in a single frame, and weaken the impact of false and missing alarms on the  ...  Then we handle the unmatched detection and tracked objects and predict matched objects' box. 3D Detection and Tracking Coupling System Tracking-Based 3D Detection Frustum Point Cloud Generation.  ... 
doi:10.1007/978-3-030-49161-1_28 fatcat:in7pp3ttsjesth4pwuyalmb3yi
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