Resumen

ALTAMIRANO ROBLES, Luis Carlos; ALTAMIRANO, Leopoldo  y  ALVARADO MENTADO, Matías. Methodologies for Reducing the Amount of Required Images Used for Articled-Object Recognition. Comp. y Sist. [online]. 2003, vol.6, n.3, pp.227-232. ISSN 2007-9737.

The appearance-based approaches are such that any object's model is made through a set of training images describing the object's appearance. In this PhD. thesis, the usage of non-uniform sampling is introduced for building this image set. Non-uniform sampling is held by a linear interpolation technique, which is used to determine the strictly necessary images. Main results are: a significant reduction in the quantity of necessary images for the object's model, as well as more precise models than those obtained by uniform sampling. Non-uniform sampling is used in conjunction with the eigenspaces technique for object recognition, producing a more efficient hybrid technique.

Palabras llave : non-uniform sampling; object recognition; appearance-based model; interpolation; eigenspaces.

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