Abstract
In this paper we showcase ImageMap - an image browsing system to visually explore and search millions of images from stock photo agencies and the like. Similar to map services like Google Maps users may navigate through multiple image layers by zooming and dragging. Zooming in (or out) shows more (or less) similar images from lower (or higher) levels. Dragging the view shows related images from the same level. Layers are organized as an image pyramid which is build using image sorting and clustering techniques. Easy image navigation is achieved because the placement of the images in the pyramid is based on an improved fused similarity calculation using visual and semantic image information. Our system also allows to perform searches. After starting an image search the user is automatically directed to a region with suiting results. This paper describes how to efficiently construct an easily navigable image pyramid even if the total number of images is huge.
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Barthel, K.U., Hezel, N., Mackowiak, R. (2015). ImageMap - Visually Browsing Millions of Images. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8936. Springer, Cham. https://doi.org/10.1007/978-3-319-14442-9_30
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DOI: https://doi.org/10.1007/978-3-319-14442-9_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14441-2
Online ISBN: 978-3-319-14442-9
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