Research groups

GC19 Artificial Vision Applications

The Research Group "Artificial Vision Applications (A.V.A.)" is a consolidated group at IMIBIC. It is constituted by 11 PhD researchers in the field of Computer Engineering. The research carried out by our group is both basic and applied. Our applied research focuses on developing solutions of Computer Vision with applications to Biomedicine. All members of the group are professors at the University of Córdoba.

Our two main interests are to address new proposals for basic research in Computer Vision, and to apply its research results to health problems involving the use of medical images.

Computer technologies in the field of Computer Vision have many potential and promising applications in health. Good examples of current trends in the field are Medical robotics and the automatic analysis of the mobility of people affected by different diseases, among many others.

In the last 5 years (2013-17) we have published more than 15 articles in JCR journals specifically in the field of Computer Vision and Pattern Recognition. Most of the publications solve basic research questions that allow developing applications to solve clinical problems. Examples of such application are patenting a human mobility analysis system and creation of a spin-off company to commercialize the product, and the development of the 3D Vision system for the surgical robot called BROCA.

We currently carry out two main projects. The first, of basic research, aims to propose new mechanisms of fusion of visual information (color, texture, key-points...) to improve 3D reconstruction processes. The second project has the objective to develop a vision system, of low cost, to ensure that the position of a patient during radiotherapy sessions is exactly the same as the position of the patient during the TAC session that will take place before the treatment and during which the specific area with tumour to be treated is planned. The vision technology we develop will be able to capture in real time and in an interactive manner the exact position of the patient’s body during the TAC session, and later guide the positioning of the patient for the radiotherapy session, thus avoiding errors in targeting the radiotherapy and radiating health tissue

Our group maintains collaborations with international research groups, including regular research stays by the group members in the different collaborating centers. Some examples of international institutions with which we collaborate are the University of Orebro (Sweden), the Technical University of Munich (Germany), the University of Malta or the INRIA Research Institute (France). In addition, we maintain regular relations with several national companies developing customized vision systems.

Research Lines

Our research in 3D scanning aims to improve current state of the art 3D scanning methods to increase robustness and reduce its price.

We aim to detect and estimate the 2D pose of humans in stereo image pairs from realistic stereo videos.

We develop new methods for Augmented Reality applications.

The goal of this research line is to estimate the 3D location of human body parts in a multi camera setup without using markers.

We aim to automatically recognize person-person interactions. We address this problem by combining visual and audio sources.

Image segmentation and edge detection are necessary steps for analysis shape. Shape of objects contain important information useful to recognize them. However, this information may contain redundant data. Polygonal approximations are an important tool useful for data reduction and object recognition.

Our research in this area aims to recognize individuals by analysing their gait



  • computer vision
  • image segmentation
  • pattern recognition
  • 3D reconstruction
  • augmented reality
  • human recognition
  • human pose estimation

Additional Information

Our website: A.V.A 

The website includes detailed information about our research, results, teaching activities, and members of the group. The contact email address for our groups is

International Award:

FOREUM Abstract Award 2019  to Juan Luis Garrido Castro by the Foundation for Research in Rheumatology.



Ongoing projects


Garrido Castro JL. Development and validation of inertial sensors applied to metrology in patients with axial spondyloarthritis. Funding Agency: Regional Ministry of Health and Social Policy (CISPS). Reference: PIN-0079-2016         


Medina Carnicer R. Muños Salinas R. Vision system for tracking and mapping, fusing markers, characteristic points, 3D information and color, and its application to 3-dimensional reconstruction and augmented reality. Funding agency: Spanish Ministry of Economy and Competitiveness (MINECO). Reference: TIN2016-75279-P

Muñoz Salinas R, Medina Carnicer R. Volumetric Measuring System. Funding agency: Spanish Ministry of Economy and Competitiveness (MINECO). Reference: RTC-2016-5661-1_01    

Finished projects

Medina Carnicer R. Sistema de Visión Artificial para posicionamiento de pacientes sometidos a Radioterapia. Funding agency: National Institute of Health Carlos III (ISCIII). Reference: IFI16/00033


Publications in 2020

Carmona-Poyato A, Fernandez-Garcia NL, Madrid-Cuevas FJ, Duran-Rosal AM. A new approach for optimal time -series segmentation ?. PATTERN RECOGNITION LETTERS. 2020. 135 ():153-159 DOI: 10.1016/j.patrec.2020.04.006 
IF: 3,255 Q: 2

Miro F, Lopez P, Vilar JM, Galisteo AM, Vivo J, Garrido-Castro JL, Gutierrez-Cepeda L. Comparative Kinematic Analysis of Hurdle Clearance Technique in Dogs: A Preliminary Report. ANIMALS. 2020. 10 (12):- DOI: 10.3390/ani10122405 
IF: 2,323 Q: 1 D: 1

Carmona-Perez C, Garrido-Castro JL, Vidal FT, Alcaraz-Clariana S, Garcia-Luque L, Alburquerque-Sendin F, Priscila Rodrigues-de-Souza D. Concurrent Validity and Reliability of an Inertial Measurement Unit for the Assessment of Craniocervical Range of Motion in Subjects with Cerebral Palsy. DIAGNOSTICS. 2020. 10 (2):- DOI: 10.3390/diagnostics10020080 
IF: 3,11 Q: 1

Carmona-Perez C, Perez-Ruiz A, Garrido-Castro JL, Vidal FT, Alcaraz-Clariana S, Garcia-Luque L, Rodrigues-de-Souza DP, Alburquerque-Sendin F. Design, Validity, and Reliability of a New Test, Based on an Inertial Measurement Unit System, for Measuring Cervical Posture and Motor Control in Children with Cerebral Palsy. DIAGNOSTICS. 2020. 10 (9):- DOI: 10.3390/diagnostics10090661 
IF: 3,11 Q: 1

Aranda-Valera IC, Garrido-Castro JL, Ladehesa-Pineda L, Vazquez-Mellado J, Zarco P, Juanola X, Gonzalez-Navas C, Font-Ugalde P, Castro-Villegas MC. How to calculate the ASDAS based on C-reactive protein without individual questions from the BASDAI: the BASDAI-based ASDAS formula. RHEUMATOLOGY. 2020. 59 (7):1545-1549 DOI: 10.1093/rheumatology/kez480 
IF: 5,606 Q: 1

Aranda-Valera IC, Cuesta-Vargas A, Garrido-Castro JL, Gardiner PV, Lopez-Medina C, Machado PM, Condell J, Connolly J, Williams JM, Munoz-Esquivel K, O'Dwyer T, Castro-Villegas MC, Gonzalez-Navas C, Collantes-Estevez E. Measuring Spinal Mobility Using an Inertial Measurement Unit System: A Validation Study in Axial Spondyloarthritis. DIAGNOSTICS. 2020. 10 (6):- DOI: 10.3390/diagnostics10060426 
IF: 3,11 Q: 1

Miro F, Galisteo AM, Garrido-Castro JL, Vivo J. Surface Electromyography of the Longissimus and Gluteus Medius Muscles in Greyhounds Walking and Trotting on Ground Flat, Up, and Downhill. ANIMALS. 2020. 10 (6):- DOI: 10.3390/ani10060968 
IF: 2,323 Q: 1 D: 1

Munoz-Salinas R, Medina-Carnicer R. UcoSLAM: Simultaneous localization and mapping by fusion of keypoints and squared planar markers. PATTERN RECOGNITION. 2020. 101 ():- DOI: 10.1016/j.patcog.2019.107193 
IF: 7,196 Q: 1 D: 1

Garcia NLF, Martinez LDM, Poyato AC, Cuevas FJM, Carnicer RM. Unsupervised generation of polygonal approximations based on the convex hull. PATTERN RECOGNITION LETTERS. 2020. 135 ():138-145 DOI: 10.1016/j.patrec.2020.04.014 
IF: 3,255 Q: 2

Gardiner PV, Small D, Munoz-Esquivel K, Condell J, Cuesta-Vargas A, Williams J, Machado PM, Garrido-Castro JL. Validity and reliability of a sensor-based electronic spinal mobility index for axial spondyloarthritis. RHEUMATOLOGY. 2020. 59 (11):3415-3423 DOI: 10.1093/rheumatology/keaa122 
IF: 5,606 Q: 1

Castro, FM; Marin-Jimenez, MJ; Guil, N; de la Blanca, N. Multimodal feature fusion for CNN-based gait recognition: an empirical comparison. NEURAL COMPUTING & APPLICATIONS. 2020. 32 (17): 14173-14193 DOI: 10.1007/s00521-020-04811-z 
IF: 4,774 Q: 1

Delgado-Escano, R; Castro, FM; Cozar, JR; Marin-Jimenez, MJ; Guil, N. MuPeG-The Multiple Person Gait Framework. SENSORS. 2020. 20 (5):- DOI: 10.3390/s20051358 
IF: 3,275 Q: 1

Delgado-Escano, R; Castro, FM; Cozar, JR; Marin-Jimenez, MJ; Guil, N; Casilari, E. A cross-dataset deep learning-based classifier for people fall detection and identification. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 2020. 184 ():- DOI: 10.1016/j.cmpb.2019.105265 
IF: 3,632 Q: 1

Publications in 2019

Munoz-Salinas R, Marin-Jimenez MJ, Medina-Carnicer R. SPM-SLAM: Simultaneous localization and mapping with squared planar markers. PATTERN RECOGNITION. 2019. 86. 156-171. DOI:10.1016/j.patcog.2018.09.003. 
IF: 5,898 D: 1

Sarmadi H, Munoz-Salinas R, Berbis MA, Medina-Carnicer R. Simultaneous Multi-View Camera Pose Estimation and Object Tracking With Squared Planar Markers. IEEE ACCESS. 2019. 7. 22927-22940. DOI:10.1109/ACCESS.2019.2896648. 
IF: 4,098 Q: 1

Munoz-Salinas R, Sarmadi H, Cazzato D, Medina-Carnicer R. Flexible body scanning without template models. SIGNAL PROCESSING. 2019. 154. 350-362. DOI:10.1016/j.sigpro.2018.09.022.
IF: 4,086 Q: 1

Duran-Rosal AM, Gutierrez PA, Carmona-Poyato A, Heryas-Martinez C; A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation. NEUROCOMPUTING. 2019. 353. (45-55). DOI: 10.1016/j.neucom.2018.05.129
IF: 4,072 Q: 1

Francisco J. Romero-Ramirez, Rafael Muñoz-Salinas, Rafael Medina-Carnicer.  Fractal Markers: A New Approach for Long-Range Marker Pose Estimation Under Occlusion. IEEE Access (2019). Volume 7. pp.  169908 - 169919. DOI: 0.1109/ACCESS.2019.2951204
IF: 4,09 Q: 1

Sarmadi H, Munoz-Salinas R, Berbis MA, Luna A, Medina-Carnicer R. 3D Reconstruction and alignment by consumer RGB-D sensors and fiducial planar markers for patient positioning in radiation therapy. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 2019. 180. DOI:10.1016/j.cmpb.2019.105004.
IF: 3,424 Q: 1

Publications in 2018

Mondejar-Guerra V, Garrido-Jurado S, Munoz-Salinas R, Marin-Jimenez MJ, Medina-Carnicer R. Robust identification of fiducial markers in challenging conditions. EXPERT SYSTEMS WITH APPLICATIONS. 2018; 93:336-345.
IF: 3,768 Q: 1 D: 1

Munoz-Salinas R, Marin-Jimenez MJ, Yeguas-Bolivar E, Medina-Carnicer R. Mapping and localization from planar markers. PATTERN RECOGNITION. 2018; 73:158-171.
IF: 3,962 Q: 1

Romero-Ramirez FJ, Munoz-Salinas R, Medina-Carnicer R. Speeded up detection of squared fiducial markers. IMAGE AND VISION COMPUTING. 2018; 76:38-47.
IF: 2,159 Q: 1

Garrido-Castro JL, Curbelo R, Mazzucchelli R, Dominguez-Gonzalez ME, Gonzalez-Navas C, Robles BJF, Zarco P, Mulero J, Cea-Calvo L, Arteaga MJ, Font-Ugalde P, Carmona L, Collantes-Estevez E. High Reproducibility of an Automated Measurement of Mobility for Patients with Axial Spondyloarthritis. JOURNAL OF RHEUMATOLOGY. 2018; 45(10):1383-1388.
IF: 3,47 Q: 2

Marin-Jimenez MJ, Romero-Ramirez FJ, Munoz-Salinas R, Medina-Carnicer R. 3D human pose estimation from depth maps using a deep combination of poses. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION. 2018; 55:627-639.
IF: 1,836 Q: 2

Lopez-Medina C, Garrido-Castro JL, Castro-Jimenez J, Gonzalez-Navas C, Calvo-Gutierrez J, Castro-Villegas MC, Ortega-Castro R, Escudero-Contreras A, Font-Ugalde P, Collantes-Estevez E. Evaluation of quality of life in patients with axial spondyloarthritis and its association with disease activity, functionality, mobility, and structural damage. CLINICAL RHEUMATOLOGY. 2018; 37(6):1581-1588.
IF: 2,141 Q: 3

Cano A, Yeguas-Bolivar E, Munoz-Salinas R, Medina-Carnicer R, Ventura S. Parallelization strategies for markerless human motion capture. JOURNAL OF REAL-TIME IMAGE PROCESSING. 2018; 14(2):453-467.
IF: 1,574 Q: 3

Publications in 2017

Carmona-Poyato A, Aguilera-Aguilera EJ, Madrid-Cuevas FJ, Marín-Jiménez MJ, Fernández-García NL. New method for obtaining optimal polygonal approximations to solve the min- ε problem. Neural Computing and Applications. 2017.28(9): 2383-2394.
IF: 2,505 Q: 2

Lopez-Quintero M, Marin-Jimenez MJ, Munoz-Salinas R, Medina-Carnicer R. Mixing body-parts model for 2D human pose estimation in stereo videos. IET COMPUTER VISION. 2017.11(6):426-433.
IF: 0,878 Q: 4

Castro FM, Marín-Jiménez MJ, Mata NG, Muñoz-Salinas R. Fisher Motion descriptor for multi-view gait recognition. International Journal of Pattern Recognition and Artificial Intelligence. 2017.31(1):-Article number 1756002.
IF: 0,994 Q: 4

Garrido-Castro JL, Gil-Cabezas J, da Silva-Grigoletto ME, Mialdea-Baena A, González-Navas C. Tridimensional kinematic characterization of female volleyball spike [Caracterización cinemática 3D del gesto técnico del remate en jugadoras de voleibol] (2017) Revista Andaluza de Medicina del Deporte, 10 (2), pp. 69-73.

Li X, González Navas C, Garrido-Castro JL. Reliability and validity of cervical mobility analysis measurement using an inertial sensor in patients with axial spondyloarthritis. Rehabilitacion. 2017. 51 (1):17-21.


Principal Investigator
Rafael Medina Carnicer

Ángel Carmona Poyato
Juan Luis Garrido Castro
Francisco José Madrid  Cuevas
Manuel Jesús Marín Jiménez
Rafael Muñoz Salinas
Nicolás Ruiz Fernández García
Enrique Yeguas Bolívar

Pre-Doctoral Researchers
David Jurado Rodríguez
Francisco José Romero Ramírez
Hamid Sarmadi