hrcak mascot   Srce   HID

Izvorni znanstveni članak

Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions

Aleš Leonardis ; Department for Pattern Recognition and Image Processing, Technical University Vienna, Vienna, Austria and Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
Horst Bischof ; Department for Pattern Recognition and Image Processing, Technical University Vienna, Vienna, Austria

Puni tekst: engleski, pdf (6 MB) str. 25-38 preuzimanja: 59* citiraj
APA 6th Edition
Leonardis, A. i Bischof, H. (1996). Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions. Journal of computing and information technology, 4 (1), 25-38. Preuzeto s https://hrcak.srce.hr/150304
MLA 8th Edition
Leonardis, Aleš i Horst Bischof. "Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions." Journal of computing and information technology, vol. 4, br. 1, 1996, str. 25-38. https://hrcak.srce.hr/150304. Citirano 24.10.2020.
Chicago 17th Edition
Leonardis, Aleš i Horst Bischof. "Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions." Journal of computing and information technology 4, br. 1 (1996): 25-38. https://hrcak.srce.hr/150304
Harvard
Leonardis, A., i Bischof, H. (1996). 'Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions', Journal of computing and information technology, 4(1), str. 25-38. Preuzeto s: https://hrcak.srce.hr/150304 (Datum pristupa: 24.10.2020.)
Vancouver
Leonardis A, Bischof H. Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions. Journal of computing and information technology [Internet]. 1996 [pristupljeno 24.10.2020.];4(1):25-38. Dostupno na: https://hrcak.srce.hr/150304
IEEE
A. Leonardis i H. Bischof, "Robust Recovery of Eigenimages in the Presence of Outliers and Occlusions", Journal of computing and information technology, vol.4, br. 1, str. 25-38, 1996. [Online]. Dostupno na: https://hrcak.srce.hr/150304. [Citirano: 24.10.2020.]

Sažetak
The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this paper we present a new approach which successfully solves these problems. The major novelty o f our approach lies in the way how the coefficients of the eigenimages are determined. Instead of computing the coefficients by a projection of the data onto the eigenimages, we extract them by a hypothesize-and-test paradigm using subsets of image points. Compeling hypotheses are then subject to a selection procedure based on the Minimum Description Length principle. The approach enables us not only to reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.

Ključne riječi
appearance-based matching; principal component analysis; robust estimation. occlusion; discrete optimization

Hrčak ID: 150304

URI
https://hrcak.srce.hr/150304

Posjeta: 115 *