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Synopsis
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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Review
This well-written monograph presents the author's research in object recognition through invariant indexing. This research work fills a void in theoretical and practical studies of computer vision. It can be used by researchers in computer object recognition and by implementors of object recognition systems. The length is just right. The presenation is clear. The index is adequate. All references are carefully selected and are cited in the text. This work is valuable from both theoretical and practical points of view, and I recommend it to readers interested in object recognition. Computing Reviews
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Object Recognition Through Invariant Indexing
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Object Recognition Through Invariant Indexing (Oxford Science Publications)
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Object Recognition through Invariant Indexing (Hardcover)
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ISBN 10: 0198565127
ISBN 13: 9780198565123
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Hardcover. Condition: new. Hardcover. 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 theidentities 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. Thebenefit of using projective measures is that they are unchanged by the imaging process. 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 and in the navigation of mobile robots. This work addresses this area of robotics research. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780198565123
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Object Recognition through Invariant Indexing (Hardcover)
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Hardcover. Condition: new. Hardcover. 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 theidentities 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. Thebenefit of using projective measures is that they are unchanged by the imaging process. 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 and in the navigation of mobile robots. This work addresses this area of robotics research. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780198565123
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Object Recognition Through Invariant Indexing
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