Dynamic vision for motion determination of Mobile Mapping System

• Autorzy: Crocetto N. , Guarnieri A. , Vettore A.
• Konferencja: Geodetic and Geodynamic Programmes of the CEI (10; EGS Symposium; 21-26.04.2002; Nice, France)
• Języki publikacji: EN

Abstrakty

EN

One of the main components of a Mobile Mapping System is represented by the Intertial Navigation Unit (INS) which along with an on-board GPS receiver allows the retreval of the van trajectory. Drifts are the main drawback of INS, affecting the overall positioning precision of the van. In order to improve its performance two solutions have been approached: 1) processing and adjustment of GPS and INS errors by Kalman filtering 2) employing of expensive INS, which leads, unfortunately , to considerable increase of the final cost of the whole system. An MMS is also tipically provided with at least two CCD cameras (color or B/N). by which the possitioning information of interesting land features can be acquired. This operation relies upon algorithms, such as camera calibration, space resection, image processing, developed for Digital Photogrammetry and Computer Vision. Given this background, in this work we propose to investigate the feasability of a dynamic model to retrieve the van motion via monocular vision, avoiding the use of INS.

Słowa kluczowe

EN

maps; GPS project; satellite navigation

PL

mapy; GPS projekt; nawigacja satelitarna

• Wydawca: Wydział Geodezji i Kartografii Politechniki Warszawskiej
• Czasopismo: Reports on Geodesy
• Rocznik: 2002
• Tom: z. 1/61
• Strony: 261--264
• Opis fizyczny: Bibliogr. 4 poz., schem.

Twórcy

autor

Crocetto N.

autor

Guarnieri A.

autor

Vettore A.

• University of Naples Italy

Bibliografia

• [1] L. Matthies, RT. Szelinski and T. Kanade, "Kalman filter-based algorithms for estimating depth from image sequences". Int. J. Of Computer Vision (1989).
• [2] P. Anadan, R. Kumar and K. Hanna, "Sdhape recovery from multiple views: a parallax based approach". Proc. Of the Image Understanding Workshop.
• [3] S. Soatto, R. Frezza and P. Perona, "Motion estimation via dynamic vision". IEEE Transaction on Automatic Control 41 (1996), no 3, pp 393-413.
• [4] T. Kailath, "Linear Systems". Prentice Hall, 1980.