Statistical methods for descriptor matching

Rubriek: Textual/Printed/Reference Materials - Boek

Prijs: € 66.99

Rating: 0/5

☆

☆

☆

☆

☆

Verzending:
Uiterlijk 31 januari in huis

Many applications, as in computer vision or medicine, aim at identifying the similarities between several images or signals. Thereafter, it is possible to detect objects, to follow them, or to overlap different pictures. In every case, the algorithmic procedures that treat the images use a selection of keypoints that they try to match by pairs. The most popular algorithm nowadays is SIFT, that performs keypoint selection, descriptor calculation, and provides a criterion for global descriptor matching. We considered changing the classical descriptor, which resulted in a shift testing problem that we solved in the minimax frame. Then, we gave a rigorous statistical formulation for the global descriptor matching problem and studied it in some special cases.

• 1 Bekijk alle specificaties

Oorspronkelijke releasedatum: 22 april 2014

Aantal pagina's: 128

Hoofdauteur: Olivier Collier

Hoofduitgeverij: Scholars' Press

Product breedte: 152 mm

Product hoogte: 8 mm

Product lengte: 229 mm

Verpakking breedte: 152 mm

Verpakking hoogte: 8 mm

Verpakking lengte: 229 mm

Verpakkingsgewicht: 200 g

EAN: 9783639715392

---