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Moving objects forecast in image sequences using autoregressive algorithms
Authors:José Luis Crespo  Marta Zorrilla  Pilar Bernardos  Eduardo Mora
Affiliation:(1) Applied Mathematics and Computer Science Department, University of Cantabria, Santander, Spain;(2) Mathematics, Statistics and Computation Department, University of Cantabria, Santander, Spain
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.
Contact Information Marta Zorrilla (Corresponding author)Email:
Keywords:Tracking and prediction  Image sequence analysis  Causal images  Autoregressive model
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