Results 281 to 290 of about 66,174 (304)
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Multiple object tracking by reliable tracklets

Signal, Image and Video Processing, 2019
This paper proposes a novel network flow model for multi-target tracking, which uses short and highly reliable detection responses as the basic unit, namely the tracklet, in the model. Our model exploits the local information of the tracklet and deploys the global strategy of data association in tracking.
Yingyi Liang   +3 more
openaire   +1 more source

Spatial Reference in Multiple Object Tracking

Experimental Psychology, 2012
Spatial reference in multiple object tracking is available from configurations of dynamic objects and static reference objects. In three experiments, we studied the use of spatial reference in tracking and in relocating targets after abrupt scene rotations.
Georg, Jahn   +3 more
openaire   +2 more sources

Analytic combinatorics in multiple object tracking

2017 Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2017
The method of analytic combinatorics (AC) is a unified approach to multiple object tracking that encodes joint probability distributions into probability generating functionals (PGFLs). PGFLs characterize distributions exactly. A high level view of the tracking applications of PGFLs is outlined in this paper. Assignment models in well-known filters are
openaire   +1 more source

Multiple Planar Object Tracking

2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023
Zhicheng Zhang   +2 more
openaire   +1 more source

Energy Minimization for Multiple Object Tracking

2014
Multiple target tracking aims at reconstructing trajectories of several moving targets in a dynamic scene, and is of significant relevance for a large number of applications. For example, predicting a pedestrian’s action may be employed to warn an inattentive driver and reduce road accidents; understanding a dynamic environment will facilitate ...
openaire   +2 more sources

A Sampling Algorithm for Tracking Multiple Objects

2000
The recently proposed CONDENSATION algorithm and its variants enable the estimation of arbitrary multi-modal posterior distributions that potentially represent multiple tracked objects. However, the specific state representation adopted in the earlier work does not explicitly supports counting, addition, deletion and occlusion of objects.
Hai Tao   +2 more
openaire   +1 more source

QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Tobias Fischer   +2 more
exaly  

Data association in multiple object tracking: A survey of recent techniques

Expert Systems With Applications, 2022
Lionel Rakai   +2 more
exaly  

Real-time multiple object tracking using deep learning methods

Neural Computing and Applications, 2021
Ioannis Daramouskas   +2 more
exaly  

Multiple Object Tracking in Deep Learning Approaches: A Survey

Electronics (Switzerland), 2021
Yesul Park, L Minh Dang, Dongil Han
exaly  

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