Abstract
In this presentation we discuss the challenges of computer vision in general search through images and videos. The point of departure is the digital content of the images, a set of 50 to 100 examples, and smart features, machine learning and computational tools to find the images best answering a one-word specification. This problem is far from being solved, yet the progress as recorded in the yearly TRECvid competitions for image search engines is impressive. We will discuss the difference between the “where” and “what” in images, discuss the need for invariance, fast computational approaches, and the state of the art in image search engines.
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© 2013 Springer-Verlag Berlin Heidelberg
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Smeulders, A. (2013). Searching Things in Large Sets of Images. In: van Emde Boas, P., Groen, F.C.A., Italiano, G.F., Nawrocki, J., Sack, H. (eds) SOFSEM 2013: Theory and Practice of Computer Science. SOFSEM 2013. Lecture Notes in Computer Science, vol 7741. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35843-2_10
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DOI: https://doi.org/10.1007/978-3-642-35843-2_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35842-5
Online ISBN: 978-3-642-35843-2
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