In this paper we present a method for motion detection and characterization using Cellular Automata. The original approach employs results of the application of the Sobel operator to individual frames, that are translated to CA configurations that are processed with the aim of detecting and characterizing moving entities to support collision avoidance from the perspective of the viewer. The paper formally describes the adopted approach as well as its experimentation videos representing plausible situations.

Carrieri, A., Crociani, L., Vizzari, G., Bandini, S. (2018). Motion Detection and Characterization in Videos with Cellular Automata. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.102-111). Springer Verlag [10.1007/978-3-319-99813-8_9].

Motion Detection and Characterization in Videos with Cellular Automata

Carrieri, A;Crociani, L
;
Vizzari, G
;
Bandini, S
2018

Abstract

In this paper we present a method for motion detection and characterization using Cellular Automata. The original approach employs results of the application of the Sobel operator to individual frames, that are translated to CA configurations that are processed with the aim of detecting and characterizing moving entities to support collision avoidance from the perspective of the viewer. The paper formally describes the adopted approach as well as its experimentation videos representing plausible situations.
paper
Cellular Automata; Motion detection; Video analysis
English
13th International Conference on Cellular Automata for Research and Industry, ACRI 2018
2018
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783319998121
2018
11115
102
111
https://www.springer.com/series/558
none
Carrieri, A., Crociani, L., Vizzari, G., Bandini, S. (2018). Motion Detection and Characterization in Videos with Cellular Automata. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.102-111). Springer Verlag [10.1007/978-3-319-99813-8_9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/218865
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