Definition
High-level concept detection is the process within which the high-level concepts or objects which are presented in a multimedia document are determined. For example, given an image, a detection scheme would reply that it contains concepts such as “sky,” “sand,” “sea,” the image depicts an “outdoor” and more specifically a “beach” scene. In some cases, the actual position of concepts within the image is also detected.
Introduction
The continuously growing volume of multimedia content has led many research efforts to high-level concept detection, since the semantics a document contains provide an effective and desirable annotation of its content. However, detecting the actual semantics within image and video documents remains still a challenging, yet unsolved problem. Its two main and most interesting aspects are the selection of the low-level features to be extracted...
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Image Segmentation is a process that divides images into regions using certain criteria of homogeneity such as color and/or texture.
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Weak classifiers are those with a nearly random performance, i.e., for a binary problem a weak classifier would have a performance slightly over 50%. With many techniques such as boosting/AdaBoost, a combination of many weak classifiers leads to a strong classifier.
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Spyrou, E., Avrithis, Y. (2008). Detection of High-Level Concepts in Multimedia. In: Furht, B. (eds) Encyclopedia of Multimedia. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78414-4_16
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DOI: https://doi.org/10.1007/978-0-387-78414-4_16
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