Übersicht			Auf mobile öffnen

Lieferstatus:	Vorankündigung
Veröffentlichung:	ANGEKÜNDIGT (Januar 2027)
Genre:	EDV / Informatik
	Absolute Visual Localization / Computer Vision / Cross-view Geo-localization (CVGL) / Data and Information Visualization / Deep Learning / GNSS-denied navigation / Informationsvisualisierung / Künstliche Intelligenz / machine learning / Maschinelles Lernen / Symbolic AI / unmanned aerial vehicles (UAV) / Visual Localization mehr...
ISBN:	9789819258734
EAN-Code:	9789819258734
Verlag:	Springer EN
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D
Seiten:	104
Illustration:	VI, 98 p. 23 illus. in color., farbige Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Keine Bewertung vor Veröffentlichung möglich.

Inhalt:

This book provides a systematic survey of unmanned aerial vehicle (UAV) visual positioning, with a primary emphasis on two central technical paths: image retrieval and image matching. These approaches lie at the heart of UAV-satellite cross-view geolocation, enabling accurate absolute positioning when GPS is unavailable or unreliable. We highlight advances in feature-based matching pipelines and deep learning-driven retrieval frameworks, which have become the most active and promising research directions. Other approaches-such as multi-sensor fusion, semantic and geometric modeling, and end-to-end learning frameworks-are briefly introduced to provide context, illustrating how UAV visual positioning is evolving into a broader ecosystem. By framing image retrieval and image matching as the core methods while situating them within the wider methodological landscape, this survey clarifies current progress, identifies open challenges, and points to future research opportunities. The intended audience includes graduate students, researchers, and engineers working on UAV navigation, computer vision, robotics, and geospatial information systems.