Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Article Citation - WoS: 28Citation - Scopus: 28A Direct Approach for Object Detection With Catadioptric Omnidirectional Cameras(Springer Verlag, 2016) Çınaroğlu, İbrahim; Baştanlar, YalınIn 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.Conference Object Citation - WoS: 21Citation - Scopus: 33A Direct Approach for Human Detection With Catadioptric Omnidirectional Cameras(Institute of Electrical and Electronics Engineers Inc., 2014) Çınaroğlu, İbrahim; Baştanlar, YalınThis paper presents an omnidirectional vision based solution to detect human beings. We first go through the conventional sliding window approaches for human detection. Then, we describe how the feature extraction step of the conventional approaches should be modified for a theoretically correct and effective use in omnidirectional cameras. In this way we perform human detection directly on the omnidirectional images without converting them to panoramic or perspective image. Our experiments, both with synthetic and real images show that the proposed approach produces successful results. © 2014 IEEE.