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An algorithm for multiple object trajectory tracking
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state at current time instance is estimated based on current and previous observations.
Mei Han +3 more
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Analytic combinatorics in multiple object tracking
2017 Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2017The 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
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Multiple object tracking by reliable tracklets
Signal, Image and Video Processing, 2019This 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
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Spatial Reference in Multiple Object Tracking
Experimental Psychology, 2012Spatial 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
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A Sampling Algorithm for Tracking Multiple Objects
2000The 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
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Energy Minimization for Multiple Object Tracking
2014Multiple 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 ...
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Multiple Object Tracking in Deep Learning Approaches: A Survey
Electronics (Switzerland), 2021Dongil Han +2 more
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Data association in multiple object tracking: A survey of recent techniques
Expert Systems With Applications, 2022Wentao Zhang +2 more
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TransCenter: Transformers With Dense Representations for Multiple-Object Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Yutong Ban +2 more
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