C. Molina, & J.B. Subirana. (1995). Reduction of complexity for object recognition algorithms.
|
J. Garcia, J.M. Sanchez, X. Orriols, & X. Binefa. (2000). Chromatic aberration and depth extraction. In 15 th International Conference on Pattern Recognition (Vol. 1, pp. 762–765).
|
A. Pujol, Juan J. Villanueva, & H. Wechsler. (2000). Automatic View Based Caricaturing. In 15 th International Conference on Pattern Recognition (Vol. 1, pp. 1072–1075).
|
Javier Varona, Jordi Gonzalez, Xavier Roca, & Juan J. Villanueva. (2000). iTrack: Image-based Probabilistic Tracking of People. In 15 th International Conference on Pattern Recognition (Vol. 3, pp. 1122–1125).
|
David Guillamet, & Jordi Vitria. (2000). A Comparison of Local versus Global Color Histograms for Object Recognition. In 15 th International Conference on Pattern Recognition (Vol. 2, pp. 422–425).
|
V. Valev, B. Sankur, & Petia Radeva. (2000). Generalized Non Reducible Descriptors. In 15 th International Conference on Pattern Recognition (Vol. 2, p. 397).
|
C. Molina, & J.B. Subirana. (1995). Polynomial-Time Algorithm for 2D object recognition. In VI National Simposium on Pattern Recognition and image Analysis.
|
J.R. Serra, S. Casadei, & J.B. Subirana. (1995). Non-Cartesian Networks for Middle Level Vision. In VI National Simposium on Pattern Recognition and image Analysis.
|
David Lloret, Joan Serrat, Antonio Lopez, A. Soler, & Juan J. Villanueva. (2000). Retinal image registration using creases as anatomical landmarks. In 15 th International Conference on Pattern Recognition (Vol. 3, pp. 207–2010).
Abstract: Retinal images are routinely used in ophthalmology to study the optical nerve head and the retina. To assess objectively the evolution of an illness, images taken at different times must be registered. Most methods so far have been designed specifically for a single image modality, like temporal series or stereo pairs of angiographies, fluorescein angiographies or scanning laser ophthalmoscope (SLO) images, which makes them prone to fail when conditions vary. In contrast, the method we propose has shown to be accurate and reliable on all the former modalities. It has been adapted from the 3D registration of CT and MR image to 2D. Relevant features (also known as landmarks) are extracted by means of a robust creaseness operator, and resulting images are iteratively transformed until a maximum in their correlation is achieved. Our method has succeeded in more than 100 pairs tried so far, in all cases including also the scaling as a parameter to be optimized
|
Xose M. Pardo, & Petia Radeva. (2000). Discriminant snakes for 3D reconstruction in medical Images. In 15 th International Conference on Pattern Recognition (Vol. 4, pp. 336–339).
|
Ricardo Toledo, X. Orriols, Petia Radeva, X. Binefa, Jordi Vitria, Cristina Cañero, et al. (2000). Eigensnakes for vessel segmentation in angiography. In 15 th International Conference on Pattern Recognition (Vol. 4, pp. 340–343).
|
A. Martinez. (1994). Disseny d´agents autonoms. Master's thesis, , .
|
A. Pujol, Felipe Lumbreras, Javier Varona, & Juan J. Villanueva. (2000). Locating people in indoor scenes for real applications. In 15 th International Conference on Pattern Recognition (Vol. 4, pp. 632–635).
|
Cristina Cañero, Petia Radeva, Ricardo Toledo, Juan J. Villanueva, & J. Mauri. (2000). 3D Curve Reconstruction by Biplane Snakes. In 15 th International Conference on Pattern Recognition (Vol. 4, pp. 563–566).
|
David Guillamet, & Jordi Vitria. (2000). Local Discriminant Regions Using Support Vector Machines for Object Recognition..
|