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Constant-time monocular object detection using scene geometry

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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.

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Acknowledgements

This work has been partially supported by the EU projects SAVASA (Grant Agreement 285621) and P-REACT (Grant Agreement 607881) under the 7th Marco Framework, and by the program Basque Government under projects IAB of the ETORGAI framework and EFITRANS of the ETORTEK framework.

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Authors and Affiliations

  1. Vicomtech-IK4, Mikeletegi 57, P. Tecnológico, San Sebastián, Spain

    Marcos Nieto, Juan Diego Ortega, Peter Leškovský & Orti Senderos

Authors
  1. Marcos Nieto
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  2. Juan Diego Ortega
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  3. Peter Leškovský
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  4. Orti Senderos
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Correspondence to Marcos Nieto.

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Nieto, M., Ortega, J.D., Leškovský, P. et al. Constant-time monocular object detection using scene geometry. Pattern Anal Applic 21, 1053–1066 (2018). https://doi.org/10.1007/s10044-017-0625-8

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  • DOI: https://doi.org/10.1007/s10044-017-0625-8

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