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Pattern Analysis and Applications

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31.05.2017 | Theoretical Advances

Constant-time monocular object detection using scene geometry

verfasst von: Marcos Nieto, Juan Diego Ortega, Peter Leškovský, Orti Senderos

Erschienen in: Pattern Analysis and Applications | Ausgabe 4/2018

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Abstract

This paper presents a structured approach for efficiently exploiting the perspective information of a scene to enhance the detection of objects in monocular systems. It defines a finite grid of 3D positions on the dominant ground plane and computes occupancy maps from which object location estimates are extracted . This method works on the top of any detection method, either pixel-wise (e.g. background subtraction) or region-wise (e.g. detection-by-classification) technique, which can be linked to the proposed scheme with minimal fine tuning. Its flexibility thus allows for applying this approach in a wide variety of applications and sectors, such as surveillance applications (e.g. person detection) or driver assistance systems (e.g. vehicle or pedestrian detection). Extensive results provide evidence of its excellent performance and its ease of use in combination with different image processing techniques.

Vorheriger Artikel A thresholding method based on interval-valued intuitionistic fuzzy sets: an application to image segmentation

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Titel: Constant-time monocular object detection using scene geometry
verfasst von: Marcos Nieto
Juan Diego Ortega
Peter Leškovský
Orti Senderos
Publikationsdatum: 31.05.2017
Verlag: Springer London
Erschienen in: Pattern Analysis and Applications / Ausgabe 4/2018
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-017-0625-8

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