Abstract
Today’s challenge in automated image retrieval is to devise a system which is able to analyse a single or sequence of images, and extract enough information to provide a meaningful description of the scene and events presented. Computer vision has been studying this problem for some 50 years, trying to solve the general “image understanding” problem within several application domains. Many techniques have been developed to analyse images and extract an abundance of information about the captured scene. In this chapter two important features are considered: the motion in the scene and the presence of human faces. Both features provide very powerful cues to understand the image or video content thus allowing to perform an automatic annotation of data for subsequent retrieval. Several approaches are discussed leaving to the reader the customisation of the proposed techniques to a given application.
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Tistarelli, M., Grosso, E. (2001). Facial and Motion Analysis for Image and Video Retrieval. In: Veltkamp, R.C., Burkhardt, H., Kriegel, HP. (eds) State-of-the-Art in Content-Based Image and Video Retrieval. Computational Imaging and Vision, vol 22. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9664-0_11
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DOI: https://doi.org/10.1007/978-94-015-9664-0_11
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