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Article Dans Une Revue Sensors Année : 2019

Track-Before-Detect Framework-Based Vehicle Monocular Vision Sensors

Résumé

This paper proposes a Track-before-Detect framework for a multibody motion segmentation (named TbD-SfM). Our contribution relies on a tightly coupled tracking before detection strategy intended to reduce the complexity of existing Multibody Structure from Motion approaches. Efforts were done towards an algorithm variant closer and aimed to a further embedded implementation for dynamic scene analysis while enhancing processing time performances. This generic motion segmentation approach can be transposed to several transportation sensor systems since no constraints are considered on segmented motions (6-DOF model). The tracking scheme is analyzed and its performance is evaluated under thorough experimental conditions including full-scale driving scenarios from known and available datasets. Results on challenging scenarios including the presence of multiple and simultaneous moving objects observed from a moving camera are reported and discussed.
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Dates et versions

hal-02007321 , version 1 (05-02-2019)

Identifiants

Citer

Hernan Gonzalez, Sergio Alberto Rodriguez Florez, Abdelhafid Elouardi. Track-Before-Detect Framework-Based Vehicle Monocular Vision Sensors. Sensors, 2019, 19 (3), pp.560. ⟨10.3390/s19030560⟩. ⟨hal-02007321⟩
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