Results 301 to 310 of about 2,547,290 (363)

ByteTrack: Multi-Object Tracking by Associating Every Detection Box

European Conference on Computer Vision, 2021
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in videos. Most methods obtain identities by associating detection boxes whose scores are higher than a threshold.
Yifu Zhang, Pei Sun, Yi Jiang, Dongdong Yu, Zehuan Yuan, Ping Luo, Wenyu Liu, Xinggang Wang   +7 more
semanticscholar   +1 more source

Incremental Learning for Robust Visual Tracking

International Journal of Computer Vision, 2008
David A. Ross, Jongwoo Lim, Ruei-Sung Lin, Ming-Hsuan Yang   +3 more
semanticscholar   +3 more sources

Track-to-track fusion of out-of-sequence tracks [PDF]

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997), 2003
Fusing out-of-sequence information is a problem of growing importance due to an increased reliance on networked sensors embedded in complicated network architectures. The problem of fusing out-of-sequence measurements (OOSM) has received some attention in literature; however, most practical fusion systems, owing to compatibility with legacy sensors and
J.A. Legg, Subhash Challa
openaire   +1 more source

Fully-Convolutional Siamese Networks for Object Tracking

ECCV Workshops, 2016
The problem of arbitrary object tracking has traditionally been tackled by learning a model of the object’s appearance exclusively online, using as sole training data the video itself.
Luca Bertinetto, Jack Valmadre, João F. Henriques, A. Vedaldi, Philip H. S. Torr   +4 more
semanticscholar   +1 more source

Transformer Tracking

Computer Vision and Pattern Recognition, 2021
Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the similarity between the template and the search region.
Xin Chen, Bin Yan, Jiawen Zhu, Dong Wang, Xiaoyun Yang, Huchuan Lu   +5 more
semanticscholar   +1 more source

High Performance Visual Tracking with Siamese Region Proposal Network

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
Bo Li, Junjie Yan, Wei Wu, Zheng Zhu, Xiaolin Hu   +4 more
semanticscholar   +1 more source

FairMOT: On the Fairness of Detection and Re-identification in Multiple Object Tracking

International Journal of Computer Vision, 2020
Multi-object tracking (MOT) is an important problem in computer vision which has a wide range of applications. Formulating MOT as multi-task learning of object detection and re-ID in a single network is appealing since it allows joint optimization of the
Yifu Zhang, Chunyu Wang, Xinggang Wang, Wenjun Zeng, Wenyu Liu   +4 more
semanticscholar   +1 more source

Tracking and track fitting

Nuclear Instruments and Methods, 1981
We generalize in several directions a previously published Runge-Kutta method for track fitting. We point out that the same basic idea applies to any equation of motion and any general method for numerical integration. For comparison we also discuss the quintic spline fit.
L. Bugge, Jan Myrheim
openaire   +2 more sources

Kernel-Based Object Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003
A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel.
D. Comaniciu, Visvanathan Ramesh, P. Meer   +2 more
semanticscholar   +1 more source