Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
In this paper we propose a general framework to solve the articulated shape matching problem, formulated as finding point-to-point correspondences between two shapes represented b...
Diana Mateus, Fabio Cuzzolin, Radu Horaud, Edmond ...
Statistical shape models have gained widespread use in medical image analysis. In order for such models to be statistically meaningful, a large number of data sets have to be inclu...
The estimation of productivity rates in cyclic construction processes is a difficult, but essential task in the planning of construction projects. The conventional method--a calcu...
Music retrieval systems for Western tonal music digital libraries have to consider rhythmic, timbral, melodic and harmonic information. Most existing retrieval systems only take i...