@article{s25010021,

title = {Reliable Disparity Estimation Using Multiocular Vision with Adjustable Baseline},

author = {Victor H. Diaz-Ramirez and Martin Gonzalez-Ruiz and Rigoberto Juarez-Salazar and Miguel Cazorla},

url = {https://www.mdpi.com/1424-8220/25/1/21},

doi = {10.3390/s25010021 keywords = stereo, computer vision, multiocular, AI},

issn = {1424-8220},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Sensors},

volume = {25},

number = {1},

abstract = {Accurate estimation of three-dimensional (3D) information from captured images is essential in numerous computer vision applications. Although binocular stereo vision has been extensively investigated for this task, its reliability is conditioned by the baseline between cameras. A larger baseline improves the resolution of disparity estimation but increases the probability of matching errors. This research presents a reliable method for disparity estimation through progressive baseline increases in multiocular vision. First, a robust rectification method for multiocular images is introduced, satisfying epipolar constraints and minimizing induced distortion. This method can improve rectification error by 25% for binocular images and 80% for multiocular images compared to well-known existing methods. Next, a dense disparity map is estimated by stereo matching from the rectified images with the shortest baseline. Afterwards, the disparity map for the subsequent images with an extended baseline is estimated within a short optimized interval, minimizing the probability of matching errors and further error propagation. This process is iterated until the disparity map for the images with the longest baseline is obtained. The proposed method increases disparity estimation accuracy by 20% for multiocular images compared to a similar existing method. The proposed approach enables accurate scene characterization and spatial point computation from disparity maps with improved resolution. The effectiveness of the proposed method is verified through exhaustive evaluations using well-known multiocular image datasets and physical scenes, achieving superior performance over similar existing methods in terms of objective measures.},

key = {computer vision, deep learning, AI},

keywords = {AI, computer vision, deep learning},

pubstate = {published},

tppubtype = {article}

}

@article{christian2022a,

title = {Towards a better performance in facial expression recognition: a data-centric approach},

author = {Christian Mejia and Miguel Cazorla and Ester Martinez-Martin},

year  = {2023},

date = {2023-01-01},

journal = {Computational Intelligence and Neuroscience},

volume = {2023},

keywords = {AI, data-centric, deep learning, facial expression recognition, performance improvement},

pubstate = {published},

tppubtype = {article}

}

@article{gomezDonoso2022c,

title = {Three-Dimensional Reconstruction Using SFM for Actual Pedestrian Classification},

author = {Francisco Gomez-Donoso and Julio Castano and Felix Escalona and Miguel Cazorla},

year  = {2023},

date = {2023-01-01},

journal = {Expert Sytems with Applications},

volume = {213},

keywords = {3D reconstruction, AI, computer vision, deep learning, pedestrian classification, structure from motion},

pubstate = {published},

tppubtype = {article}

}

@article{mejia2023,

title = {Improving Facial Expression Recognition through Data Preparation & Merging},

author = {Christian Mejia-Escobar and Miguel Cazorla and Ester Martinez-Martin},

year  = {2023},

date = {2023-01-01},

journal = {IEEE Access},

volume = {Accepted},

keywords = {AI, deep learning, emotion detection},

pubstate = {published},

tppubtype = {article}

}

@article{alvarez2023,

title = {Exploring Transferability on Adversarial Attacks},

author = {Enrique Alvarez and Rafael Alvarez Sanchez and Miguel Cazorla},

year  = {2023},

date = {2023-01-01},

journal = {IEEE Access},

volume = {Accepted},

keywords = {adversarial attacks, AI, deep learning},

pubstate = {published},

tppubtype = {article}

}

@article{marquez2023artificial,

title = {Artificial Intelligence-based System for Detecting Attention Levels in Students},

author = {Luis Marquez-Carpintero and Monica Pina-Navarro and Sergio Suescun-Ferrandiz and Felix Escalona and Francisco Gomez-Donoso and Rosabel Roig-Vila and Miguel Cazorla},

year  = {2023},

date = {2023-01-01},

journal = {Journal of visualized experiments: JoVE},

number = {202},

keywords = {AI, deep learning, Education, emotion detection},

pubstate = {published},

tppubtype = {article}

}

@article{torres2023,

title = {A Malware Detection Approach Based on Feature Engineering and Behavior Analysis},

author = {Manuel Torres Mendoza and Rafael Alvarez Sanchez and Miguel Cazorla},

year  = {2023},

date = {2023-01-01},

journal = {IEEE Access},

volume = {Accepted},

keywords = {AI, deep learning, security},

pubstate = {published},

tppubtype = {article}

}

@article{9701312,

title = {3DSliceLeNet: Recognizing 3D Objects Using a Slice-Representation},

author = {Francisco Gomez-Donoso and Felix Escalona and Sergio Orts-Escolano and Alberto Garcia-Garcia and Jose Garcia-Rodriguez and Miguel Cazorla},

doi = {10.1109/ACCESS.2022.3148387},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Access},

volume = {10},

pages = {15378-15392},

keywords = {3D object recognition, AI, computer vision, deep learning},

pubstate = {published},

tppubtype = {article}

}

@article{Rangel2022,

title = {Automatic understanding and mapping of regions in cities using Google},

author = {Jose Carlos Rangel and Edmanuel Cruz and Miguel Cazorla},

year  = {2022},

date = {2022-01-01},

journal = {Applied Sciences},

volume = {12},

number = {6},

keywords = {AI, automatic mapping, city analytics, deep learning, urban regions},

pubstate = {published},

tppubtype = {article}

}

@article{Donoso2021a,

title = {Accurate Multilevel Classification for Wildlife Images},

author = {Francisco Gomez-Donoso and Felix Escalona and F. Perez-Esteve and Miguel Cazorla},

year  = {2021},

date = {2021-01-01},

journal = {Computational Intelligence and Neuroscience},

volume = {2021},

keywords = {AI, deep learning, multilevel, wildlife classification},

pubstate = {published},

tppubtype = {article}

}

@article{martinez-martin2021a,

title = {Deep Learning Techniques for Spanish Sign Language Interpretation},

author = {Ester Martinez-Martin and Francisco Morillas-Espejo},

doi = {https://doi.org/10.1155/2021/5532580},

year  = {2021},

date = {2021-01-01},

journal = {Computational Intelligence and Neuroscience},

volume = {2021},

keywords = {AI, deep learning, gesture interpretation, Spanish sign language},

pubstate = {published},

tppubtype = {article}

}

@article{combaho2019,

title = {COMBAHO: A Deep Learning system for Integrating Brain Injury Patients in society},

author = {Jose Garcia-Rodriguez and Francisco Gomez-Donoso and Alberto Garcia-Garcia and Miguel Cazorla and Sergio Orts-Escolano and Oprea and Zuria Bauer and John Castro-Vargas and Pablo Martinez-Gonzalez and David Ivorra-Piqueres and Felix Escalona and Eugenio Aguirre and Miguel Garcia-silviente and Marcelo Garcia-Perez and Jose M Canyas and Francisco Martin-Rico and Jonathan Gines and Francisco Rivas-Montero},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Pattern Recognition Letters},

volume = {137},

pages = {80-90},

keywords = {AI, assistive technology, brain injury, deep learning, social integration},

pubstate = {published},

tppubtype = {article}

}

@article{rompetechos2019,

title = {Enhancing Perception for the Visually Impaired with Deep Learning Techniques and Low-cost Wearable Sensors},

author = {Zuria Bauer and Alejandro Dominguez and Edmanuel Cruz and Francisco Gomez-Donoso and Sergio Orts-Escolano and Miguel Cazorla},

year  = {2020},

date = {2020-01-01},

journal = {Pattern Recognition Letters},

volume = {137},

pages = {27-36},

keywords = {AI, deep learning, enhanced perception, visually impaired, wearable sensors},

pubstate = {published},

tppubtype = {article}

}

@article{Cruz2020AI,

title = {How to add new knowledge to already trained deep learning models applied to semantic localization},

author = {Edmanuel Cruz and Jose Carlos Rangel and Francisco Gomez-Donoso and Miguel Cazorla},

year  = {2020},

date = {2020-01-01},

journal = {Applied Intelligence},

volume = {50},

number = {1},

pages = {14-28},

keywords = {AI, deep learning, semantic localization, transfer learning},

pubstate = {published},

tppubtype = {article}

}

@article{Espinosa20,

title = {Biomarker Localization from Deep Learning Regression Networks},

author = {Carlos Cano-Espinosa and German Gonzalez-Serrano and George R. Washko and Miguel Cazorla and Raul San Jose Estepar},

year  = {2020},

date = {2020-01-01},

journal = {IEEE Transactions on Medical Imaging},

volume = {39},

number = {6},

pages = {2121-2132},

keywords = {AI, biomarker localization, deep learning, medical imaging},

pubstate = {published},

tppubtype = {article}

}

@article{cano2020computer,

title = {Computer aided detection of pulmonary embolism using multi-slice multi-axial segmentation},

author = {Carlos Cano-Espinosa and Miguel Cazorla and German Gonzalez-Serrano},

year  = {2020},

date = {2020-01-01},

journal = {Applied Sciences},

volume = {10},

number = {8},

pages = {2945},

publisher = {MDPI},

keywords = {AI, computer-aided detection, deep learning, multi-axial segmentation, pulmonary embolism},

pubstate = {published},

tppubtype = {article}

}

@article{martinez2020machine,

title = {Machine learning techniques for assistive robotics},

author = {Ester Martinez-Martin and Miguel Cazorla and Sergio Orts-Escolano},

year  = {2020},

date = {2020-01-01},

journal = {Electronics},

volume = {9},

number = {5},

pages = {821},

publisher = {MDPI},

keywords = {AI, assistive robotics, deep learning, healthcare, machine learning},

pubstate = {published},

tppubtype = {article}

}

@article{Nadia2020,

title = {A sEMG-controlled 3D game for rehabilitation therapies: real-time hand gesture recognition using deep learning techniques},

author = {Nadia Nasri and Sergio Orts-Escolano and Miguel Cazorla},

year  = {2020},

date = {2020-01-01},

journal = {Sensors},

volume = {20},

number = {22},

keywords = {AI, deep learning, hand gesture recognition, rehabilitation game, sEMG},

pubstate = {published},

tppubtype = {article}

}

@article{martin2020semantic,

title = {Semantic visual recognition in a cognitive architecture for social robots},

author = {Francisco Martin-Rico and Francisco Gomez-Donoso and Felix Escalona and Jose Garcia-Rodriguez and Miguel Cazorla},

year  = {2020},

date = {2020-01-01},

journal = {Integrated Computer-Aided Engineering},

volume = {27},

number = {3},

pages = {301-316},

publisher = {SAGE Publications Sage UK: London, England},

keywords = {AI, cognitive architecture, deep learning, semantic visual recognition, social robots},

pubstate = {published},

tppubtype = {article}

}

@article{Rangel2018b,

title = {Automatic semantic Maps Generation from Lexical Annotations},

author = {Jose Carlos Rangel and Miguel Cazorla and Ismael Garcia-Varea and Cristina Romero-Gonzalez and Jesus Martinez-Gomez},

year  = {2019},

date = {2019-01-01},

journal = {Autonomous robots},

volume = {43},

number = {3},

pages = {697-712},

keywords = {AI, deep learning, lexical annotations, robotics, semantic maps},

pubstate = {published},

tppubtype = {article}

}

@article{8936685,

title = {Refining the Fusion of Pepper Robot and Estimated Depth Maps Method for Improved 3D Perception},

author = {Zuria Bauer and Felix Escalona and Edmanuel Cruz and Miguel Cazorla and Francisco Gomez-Donoso},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Access},

volume = {7},

pages = {185076-185085},

keywords = {3D perception, AI, deep learning, depth estimation, Pepper robot, sensor fusion},

pubstate = {published},

tppubtype = {article}

}

@article{Gonzalez2019,

title = {Biomedical Image Processing with Containers and Deep Learning: An Automated Analysis Pipeline},

author = {German Gonzalez-Serrano and Conor L. Evans},

doi = {10.1002/bies.201900004},

issn = {15211878},

year  = {2019},

date = {2019-01-01},

journal = {BioEssays},

volume = {41},

issue = {6},

abstract = {...},

keywords = {AI, automation, big data, containers, deep learning, image processing},

pubstate = {published},

tppubtype = {article}

}

@article{DonosoIMAVIs2018,

title = {Large-scale Multiview 3D Hand Pose Dataset},

author = {Francisco Gomez-Donoso and Sergio Orts-Escolano and Miguel Cazorla},

year  = {2019},

date = {2019-01-01},

journal = {Image and Vision Computing},

volume = {81},

pages = {25-33},

keywords = {3D hand pose, AI, deep learning, large-scale, multiview dataset},

pubstate = {published},

tppubtype = {article}

}

@article{gomez2019enhancing,

title = {Enhancing the ambient assisted living capabilities with a mobile robot},

author = {Francisco Gomez-Donoso and Felix Escalona and Francisco Miguel Rivas and Jose Maria Canyas and Miguel Cazorla},

year  = {2019},

date = {2019-01-01},

journal = {Computational intelligence and neuroscience},

volume = {2019},

publisher = {Hindawi},

keywords = {AI, ambient assisted living, assistive robotics, deep learning, mobile robot},

pubstate = {published},

tppubtype = {article}

}

@article{cinMadrid2019,

title = {Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot},

author = {Francisco Gomez-Donoso and Felix Escalona and Francisco Rivas-Montero and Jose M. Canyas and Miguel Cazorla},

year  = {2019},

date = {2019-01-01},

journal = {Computational Intelligence and Neuroscience},

volume = {2019},

keywords = {AI, ambient assisted living, deep learning, indoor navigation, mobile robot},

pubstate = {published},

tppubtype = {article}

}

@article{Gonzalez2018Reply,

title = {Reply to Mummadi et al.: Overfitting and Use of Mismatched Cohorts in Deep Learning Models: Preventable Design Limitations},

author = {German Gonzalez-Serrano and Samuel Y. Ash and Raul San Jose Estepar and George Washko},

url = {https://pubmed.ncbi.nlm.nih.gov/29641211/},

doi = {10.1164/RCCM.201803-0540LE},

issn = {1535-4970},

year  = {2018},

date = {2018-01-01},

journal = {American journal of respiratory and critical care medicine},

volume = {198},

issue = {4},

pages = {545},

publisher = {Am J Respir Crit Care Med},

keywords = {AI, commentary, deep learning, mismatched cohorts, overfitting},

pubstate = {published},

tppubtype = {article}

}

@article{Rangel2018,

title = {semi-supervised 3D Object Recognition through CNN Labeling},

author = {Jose Carlos Rangel and J. Martinez Gomez and C. Romero Gonzalez and I. Garcia Varea and Miguel Cazorla},

doi = {https://doi.org/10.1016/j.asoc.2018.02.005},

year  = {2018},

date = {2018-01-01},

journal = {Applied soft Computing},

volume = {65},

pages = {603-613},

keywords = {3D object recognition, AI, deep learning, semi-supervised},

pubstate = {published},

tppubtype = {article}

}