Object Recognition Through Invariant Indexing
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Computer (robot) vision is a very challenging area of research. The problem of object recognition is central to computer vision in many applications such as the automatic sorting , selection, orientation, and inspection of manufactured items. It is also very important in navigation problems in mobile robots. In invarient indexing one computes measures from a scene that index into a base with a minimal search, so producing hypotheses of the identities of objects present in the scene. This book investigates how these measures are incorporated into a recognition system and also develops a range o...
Computer (robot) vision is a very challenging area of research. The problem of object recognition is central to computer vision in many applications such as the automatic sorting , selection, orientation, and inspection of manufactured items. It is also very important in navigation problems in mobile robots. In invarient indexing one computes measures from a scene that index into a base with a minimal search, so producing hypotheses of the identities of objects present in the scene. This book investigates how these measures are incorporated into a recognition system and also develops a range of projective indexes that can be used. The benefit of using projective measures is that they are unchanged by the imaging process.
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