Biomedical subjects

Cordelia Schmid

Publications and source records attributed to Cordelia Schmid.

3 recordsLinked to original sources

PubMed2007

Segmenting, modeling, and matching video clips containing multiple moving objects.

This paper presents a novel representation for dynamic scenes composed of multiple rigid objects that may undergo different motions and are observed by a moving camera. Multiview constraints associated with groups of affine-covariant scene patches and a normalized description of their appearance are used to segment a scene into its rigid components, construct three-dimensional models of these components, and match instances of models recovered from different image sequences. The proposed approach has been applied to the detection and matching of moving objects in video sequences and to shot matching, i.e., the identification of shots that depict the same scene in a video clip.

Algorithms↗

PubMed2005

A sparse texture representation using local affine regions.

This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine Harris and Laplacian regions is found in the image. Each of these regions can be thought of as a texture element having a characteristic elliptic shape and a distinctive appearance pattern. This pattern is captured in an affine-invariant fashion via a process of shape normalization followed by the computation of two novel descriptors, the spin image and the RIFT descriptor. When affine invariance is not required, the original elliptical shape servee as an additional discriminative feature for texture recognition. The proposed approach is evaluated in retrieval and classification tasks using the entire Brodatz database and a publicly available collection of 1,000 photographs of textured surfaces taken from different viewpoints.

Algorithms↗

PubMed2005

Performance evaluation of local descriptors.

In this paper, we compare the performance of descriptors computed for local interest regions, as, for example, extracted by the Harris-Affine detector. Many different descriptors have been proposed in the literature. It is unclear which descriptors are more appropriate and how their performance depends on the interest region detector. The descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the detector. Our evaluation uses as criterion recall with respect to precision and is carried out for different image transformations. We compare shape context, steerable filters, PCA-SIFT, differential invariants, spin images, SIFT, complex filters, moment invariants, and cross-correlation for different types of interest regions. We also propose an extension of the SIFT descriptor and show that it outperforms the original method. Furthermore, we observe that the ranking of the descriptors is mostly independent of the interest region detector and that the SIFT-based descriptors perform best. Moments and steerable filters show the best performance among the low dimensional descriptors.

Algorithms↗