Rank-1 tensor approximation for high-order association in multi-target tracking

DOI10.1007/s11263-018-01147-zzbMath1477.68423OpenAlexW2911621419MaRDI QIDQ2193819

Xinchu Shi, Haibin Ling, Weiming Hu, Peng Chu, Junliang Xing, Y. Pang

Publication date: 20 August 2020

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11263-018-01147-z

zbMATH Keywords

multi-target trackingdata associationmulti-dimensional assignmentrank-1 tensor approximation

Mathematics Subject Classification ID

Multilinear algebra, tensor calculus (15A69) Machine vision and scene understanding (68T45)

Uses Software

• KITTI

Cites Work

• Unnamed Item
• Multi-target tracking by online learning a CRF model of appearance and motion patterns
• Tracking and data association
• Multidimensional assignment formulation of data association problems arising from multitarget and multisensor tracking
• On the Best Rank-1 and Rank-(R₁ ,R₂ ,. . .,R_N) Approximation of Higher-Order Tensors
• Markov Chain Monte Carlo Data Association for Multi-Target Tracking
• A Relationship Between Arbitrary Positive Matrices and Doubly Stochastic Matrices
• Computer Vision - ECCV 2004

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