Vision based image retrieval (VBIR): a new eye tracking based approach to efficient and intuitive image retrieval

Die vorliegende Arbeit beschreibt einen neuen Ansatz fur die inhaltsbasierte Suche von Bildern in Datenbanken auf Basis von Blickbewegungsmessungen. Im Vision-Based Image Retrieval (VBIR) werden die Bilder in 16 gleich grose Sektoren unterteilt, fur die jeweils lokale Farb-, Form- und Texturmerkmale berechnet werden. Das Besondere am VBIR-Ansatz ist die dynamische Gewichtung lokaler Bildmerkmale (Bottom-Up Informationen) aus Aufmerksamkeitslandschaften online erfasster Blickdaten (Top-Down Informationen). Auf diese Weise passt sich das System den Praferenzen des Benutzers an. In den folgenden Suchprozessen werden dann solche Bilder ausgewahlt, die dem gesuchten Bild in den bevorzugten Sektoren und Bildeigenschaften am ahnlichsten sind. Das neue System wurde in zwei Studien evaluiert, deren Ergebnisse vorgestellt werden: zum einen wird der neue Ansatz mit einem klassischen Bildsuchsystem (CBIR) verglichen. Zum anderen werden die Suchergebnisse beider Ansatze gemas menschlichen Ahnlichkeitsbewertungen beurteilt. Die Ergebnisse belegen, dass mit dem VBIR-System eine hohere Erfolgsquote bei kurzeren mittleren Suchzeiten erreicht werden kann. Daruber hinaus werden die gefundenen Bilder als ahnlicher zum Anfragebild bewertet als beim CBIR-System. Bei der Umsetzung der Bildsuchsysteme werden zwei zentrale Aspekte fur deren Gestaltungsprozess, namlich die Bestimmung der optimalen Gewichtung der Bildmerkmale und die Merkmalsevaluierung, genauer untersucht. Dabei wird die optimale Gewichtung der eingesetzten Merkmalstypen mittels Shannon-Entropie aus Distanzhistogrammen berechnet. Im Gegensatz zu den ublichen Ansatzen, die iterativ die Einzelgewichtungen manuell anpassen, erfordert dieses Verfahren lediglich einen Rechendurchgang. Die Evaluation der Bildmerkmale erfolgt uber ein Lernverfahren, eine Selbstorganisierende Merkmalskarte (SOM), welche Bilder gemas ihrer Merkmalsahnlichkeit auf einem 2D Gitter anordnet. Die Arbeit schliest mit der Beschreibung von Computermodellen, mit denen die Suchprozesse fur beide Bildsuchverfahren (VBIR und CBIR) in wesentlichen Zugen nachgebildet werden. Mittels eines weiteren, separaten Modells wird evaluiert, wie die verschiedenen Bildeigenschaften die Aufmerksamkeit der Probanden steuern.

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