Motion analysis and speed estimation from video signals is a topic of increasing interest, e.g., in the field of traffic monitoring and road surveillance. Moving objects in a considered video sequence may undergo several modifications either due to perspectival issues, that depend on the camera placement, or periodic behaviours. Hence, geometrical transformations, such as scaling and rotations, and periodic features are often superimposed to the motion of an object of interest. In this paper we present a novel method to speed estimation that applies to video streams framing multiple objects which experience a dynamic change throughout the video duration. Applications and results are presented to assess the robustness of the proposed algorithm.

On Motion Analysis of Multiple Time-Variant Objects in Video Sequences / Mattioli, V.; Alinovi, D.; Raheli, R.. - ELETTRONICO. - (2020), pp. 445-448. ((Intervento presentato al convegno 43rd International Conference on Telecommunications and Signal Processing, TSP 2020 tenutosi a ita nel 2020 [10.1109/TSP49548.2020.9163577].

On Motion Analysis of Multiple Time-Variant Objects in Video Sequences

Mattioli V.;Alinovi D.;Raheli R.
2020

Abstract

Motion analysis and speed estimation from video signals is a topic of increasing interest, e.g., in the field of traffic monitoring and road surveillance. Moving objects in a considered video sequence may undergo several modifications either due to perspectival issues, that depend on the camera placement, or periodic behaviours. Hence, geometrical transformations, such as scaling and rotations, and periodic features are often superimposed to the motion of an object of interest. In this paper we present a novel method to speed estimation that applies to video streams framing multiple objects which experience a dynamic change throughout the video duration. Applications and results are presented to assess the robustness of the proposed algorithm.
978-1-7281-6376-5
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2886704
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