SURVEY OF APPEARANCE-BASED METHODS FOR OBJECT RECOGNITION
SURVEY OF APPEARANCE-BASED METHODS FOR OBJECT RECOGNITION
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发表时间：
2008
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通讯作者：
P. Roth;M. Winter
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作者：
P. Roth;M. Winter
In this survey we give a short introduction into appearance-based object recognition. In general, one distinguishes between two different strategies, namely local and global approaches. Local approaches search for salient regions characterized by e.g. corners, edges, or entropy. In a later stage, these regions are characterized by a proper descriptor. For object recognition purposes the thus obtained local representations of test images are compared to the representations of previously learned training images. In contrast to that, global approaches model the information of a whole image. In this report we give an overview of well known and widely used region of interest detectors and descriptors (i.e, local approaches) as well as of the most important subspace methods (i.e., global approaches). Note, that the discussion is reduced to methods, that use only the gray-value information of an image.
