Dr.  SALVI MAS, JOAQUIN

Plana personal

Categoria:
CATEDRÀTIC D'UNIVERSITAT
Departament:
ARQUITECTURA I TECNOLOGIA DE COMPUTADORS
Àrea de coneixement:
ARQUITECTURA I TECNOLOGIA DE COMPUTADORS
Institut:
INSTITUT DE RECERCA EN VISIÓ PER COMPUTADOR I ROBÒTICA (VICOROB)
Grup de recerca:
Visió per computador i robòtica - Vicorob
ORCID PRC:
0000-0002-9482-7126

Software programat

The code may be downloaded, used, modified and distributed for research purposes with acknowledgement of the author. Please cite the corresponding paper if you use the code/data here available.

Camera Calibration toolbox. The toolbox contains the camera calibration methods explained in the paper.

The paper: J. Salvi, X. Armangué, J. Batlle. A Comparative Review of Camera Calibrating Methods with Accuracy Evaluation. Pattern Recognition 35(7), pp 1617-1635, July 2002.

Fundamental Matrix Estimation toolbox: The toolbox contains the fundamental matrix computation methods explained in the paper.

The paper: X. Armangué, J. Salvi. Overall View Regarding Fundamental Matrix Estimation. Image and Vision Computing 21(2), pp 205-220, February 2003.

3D Coded Structured Light Acquisition toolbox: The toolbox contains the implementation of the Monks method explained in the following paper.

The paper: J. Salvi, J. Pagés, J. Batlle. Pattern Codification Strategies in Structured Light Systems. Pattern Recognition 37(4), pp 827-849, April 2004.

Pair-wise Multi-view Point-Cloud Registration toolbox: The toolbox contains some of the registration methods explained in the following papers.

The papers:

J. Salvi, B. Batlle, C. Matabosch, X. Lladó. Overview of Surface Registration Techniques Including Loop Minimization for 3D Modelling and Visual Inspection. Journal of Electronic Imaging 17(3), 031103, 2008.

J. Salvi, C. Matabosch, D. Fofi and J. Forest. A review of Recent Range Image Registration Methods with Accuracy Evaluation. Image and Vision Computing 25, pp 578-596, 2007.

Simultaneous Localization and Mapping toolbox. This toolbox includes the cases of one robot moving in one dimension (1D), two dimensions (2D) and three dimensions (3D) with different potential situations in which either the position and/or the velocity of the robot are measured together with detected landmarks. The toolbox might be used as an introduction to Kalman Filtering in SLAM.

The papers:

J. Aulinas, Y.R. Petillot, J. Salvi, X. Lladó. The SLAM Problem: A Survey. 11th International Conference of the Catalan Association for Artificial Intelligence, CCIA'08, Sant Martí d'Empúries (Spain) October 22-24, 2008. Frontiers in Artificial Intelligence and Applications, vol. 184, pp 363-371, 2008.

J. Salvi, Y. Petillot, B. Batlle. Visual SLAM for 3D Large-Scale Seabed Acquisition Employing Underwater Vehicles. IEEE International Conference on Intelligent Robots and Systems, IROS'08, pp 1011-1016, Nice (France) September 22-26, 2008.