AG-Mono: A Monocular Dataset for Unmanned Air Vehicles AG-Mono: Insansiz Hava Araçlari için Monoküler Görüntü Veri Kümesi


Simsek B., Giden I. H., Bilge H. Ş.

30th Signal Processing and Communications Applications Conference, SIU 2022, Safranbolu, Türkiye, 15 - 18 Mayıs 2022 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu55565.2022.9864725
  • Basıldığı Şehir: Safranbolu
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Monocular Image Dataset, Unmanned Aerial Vehicles (UAVs), Visual SLAM (vSLAM)
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2022 IEEE.One of the most important information needed while performing unmanned aerial vehicles (UAV) operations is about the platform location and the environment. Such platforms mostly use GNSS signals outdoors. However, in indoor areas where GNSS signals cannot be received or in situations where signals are jammed, it is not possible to obtain location information using these signals. For that reason, alternative navigation systems have become so crucial. One of the most preferred systems among navigation technologies is the visual simultaneous localization and mapping (vSLAM) method performed using RGB cameras on the UAVs. In this study, an open monocular image dataset called AG-Mono was created and published online to test the performance of vSLAM algorithms. This dataset was created at three different exposure times using a handheld platform, and it includes video sequences at 640x480 image resolution. The experimental area where the images were created is a closed corridor with 16.5 x 4.5 meters and four sharp corners.