6 August 1993 Target-motion modeling based on time series and Kalman filtering
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Proceedings Volume 2064, Machine Vision Applications, Architectures, and Systems Integration II; (1993); doi: 10.1117/12.150314
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States
Abstract
This paper introduces the main issues involved in modelling the motion of a target that evolves in a 3D environment and presents a new approach to this sort of problem. The results are compared to those obtained through a whole family of polynomial curve-fitting algorithms based on statistical optimization and those called SMOP and MOCPA.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sergi Casas, Gabriel A. Oliver, Joan Frau, R. Planas, Joseph Fernandez, "Target-motion modeling based on time series and Kalman filtering", Proc. SPIE 2064, Machine Vision Applications, Architectures, and Systems Integration II, (6 August 1993); doi: 10.1117/12.150314; https://doi.org/10.1117/12.150314
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KEYWORDS
Motion models

Autoregressive models

Data modeling

Filtering (signal processing)

Modeling

Detection and tracking algorithms

Motion estimation

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