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Moving objects forecast in image sequences using autoregressive algorithms

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Abstract

The objective of this paper is to present an overall approach to forecasting the future position of the moving objects of an image sequence after processing the images previous to it. The proposed method makes use of classical techniques such as optical flow to extract objects’ trajectories and velocities, and autoregressive algorithms to build the predictive model. Our method can be used in a variety of applications, where videos with stationary cameras are used, moving objects are not deformed and change their position with time. One of these applications is traffic control, which is used in this paper as a case study with different meteorological conditions to compare with.

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Authors and Affiliations

  1. Applied Mathematics and Computer Science Department, University of Cantabria, Santander, Spain

    José Luis Crespo, Pilar Bernardos & Eduardo Mora

  2. Mathematics, Statistics and Computation Department, University of Cantabria, Santander, Spain

    Marta Zorrilla

Authors
  1. José Luis Crespo
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  2. Marta Zorrilla
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  3. Pilar Bernardos
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  4. Eduardo Mora
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Correspondence to Marta Zorrilla.

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Crespo, J.L., Zorrilla, M., Bernardos, P. et al. Moving objects forecast in image sequences using autoregressive algorithms. Vis Comput 25, 309–323 (2009). https://doi.org/10.1007/s00371-008-0270-8

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