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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Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.
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Hardcover. Condición: 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. Nº de ref. del artículo: 9780198565123
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Hardcover. Condición: 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. Nº de ref. del artículo: 9780198565123
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