Signal, Image and Video Processing

, Volume 10, Issue 2, pp 413–420 | Cite as

A direct approach for object detection with catadioptric omnidirectional cameras

Original Paper

Abstract

In this paper, we present an omnidirectional vision-based method for object detection. We first adopt the conventional camera approach that uses sliding windows and histogram of oriented gradients (HOG) features. Then, we describe how the feature extraction step of the conventional approach should be modified for a theoretically correct and effective use in omnidirectional cameras. Main steps are modification of gradient magnitudes using Riemannian metric and conversion of gradient orientations to form an omnidirectional sliding window. In this way, we perform object detection directly on the omnidirectional images without converting them to panoramic or perspective images. Our experiments, with synthetic and real images, compare the proposed approach with regular (unmodified) HOG computation on both omnidirectional and panoramic images. Results show that the proposed approach should be preferred.

Keywords

Catadioptric omnidirectional cameras Object detection  Human detection Car detection Vehicle detection  

Supplementary material

11760_2015_768_MOESM1_ESM.pdf (196 kb)
Supplementary material 1 (pdf 195 KB)
11760_2015_768_MOESM2_ESM.pdf (912 kb)
Supplementary material 2 (pdf 912 KB)

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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Computer Engineering DepartmentIzmir Institute of TechnologyIzmirTurkey

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