The increasing amount of information available in today's world raises the need to retrieve relevant data efficiently. Unlike text-based retrieval, where keywords are successfully used to index into documents, content-based image retrieval poses up front the fundamental questions how to extract...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Rubner, Yossi (VerfasserIn), Tomasi, Carlo (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Boston, MA Springer US 2001
Schriftenreihe:	The Springer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors 594
Schlagworte:	Engineering Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Data Structures, Cryptology and Information Theory Data structures (Computer science) Artificial intelligence Image processing Control engineering Robotics Mechatronics
Online-Zugang:	FHI01 BTU01 Volltext
Zusammenfassung:	The increasing amount of information available in today's world raises the need to retrieve relevant data efficiently. Unlike text-based retrieval, where keywords are successfully used to index into documents, content-based image retrieval poses up front the fundamental questions how to extract useful image features and how to use them for intuitive retrieval. We present a novel approach to the problem of navigating through a collection of images for the purpose of image retrieval, which leads to a new paradigm for image database search. We summarize the appearance of images by distributions of color or texture features, and we define a metric between any two such distributions. This metric, which we call the "Earth Mover's Distance" (EMD), represents the least amount of work that is needed to rearrange the mass is one distribution in order to obtain the other. We show that the EMD matches perceptual dissimilarity better than other dissimilarity measures, and argue that it has many desirable properties for image retrieval. Using this metric, we employ Multi-Dimensional Scaling techniques to embed a group of images as points in a two- or three-dimensional Euclidean space so that their distances reflect image dissimilarities as well as possible. Such geometric embeddings exhibit the structure in the image set at hand, allowing the user to understand better the result of a database query and to refine the query in a perceptually intuitive way
Beschreibung:	1 Online-Ressource (XXIII, 137 p)
ISBN:	9781475733433
DOI:	10.1007/978-1-4757-3343-3