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233 results on '"de la Escalera, Arturo"'

1. Joint object detection and re-identification for 3D obstacle multi-camera systems

Author

Cortés, Irene, Beltrán, Jorge, de la Escalera, Arturo, and García, Fernando

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In recent years, the field of autonomous driving has witnessed remarkable advancements, driven by the integration of a multitude of sensors, including cameras and LiDAR systems, in different prototypes. However, with the proliferation of sensor data comes the pressing need for more sophisticated information processing techniques. This research paper introduces a novel modification to an object detection network that uses camera and lidar information, incorporating an additional branch designed for the task of re-identifying objects across adjacent cameras within the same vehicle while elevating the quality of the baseline 3D object detection outcomes. The proposed methodology employs a two-step detection pipeline: initially, an object detection network is employed, followed by a 3D box estimator that operates on the filtered point cloud generated from the network's detections. Extensive experimental evaluations encompassing both 2D and 3D domains validate the effectiveness of the proposed approach and the results underscore the superiority of this method over traditional Non-Maximum Suppression (NMS) techniques, with an improvement of more than 5\% in the car category in the overlapping areas.

Published
2023

2. Automated Defect Recognition of Castings defects using Neural Networks

Author

García-Pérez, Alberto, Gómez-Silva, María José, and de la Escalera, Arturo

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Industrial X-ray analysis is common in aerospace, automotive or nuclear industries where structural integrity of some parts needs to be guaranteed. However, the interpretation of radiographic images is sometimes difficult and may lead to two experts disagree on defect classification. The Automated Defect Recognition (ADR) system presented herein will reduce the analysis time and will also help reducing the subjective interpretation of the defects while increasing the reliability of the human inspector. Our Convolutional Neural Network (CNN) model achieves 94.2\% accuracy (mAP@IoU=50\%), which is considered as similar to expected human performance, when applied to an automotive aluminium castings dataset (GDXray), exceeding current state of the art for this dataset. On an industrial environment, its inference time is less than 400 ms per DICOM image, so it can be installed on production facilities with no impact on delivery time. In addition, an ablation study of the main hyper-parameters to optimise model accuracy from the initial baseline result of 75\% mAP up to 94.2\% mAP, was also conducted., Comment: This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections. The Version of Record of this article is published in Journal of Nondestructive Evaluation, and is available online at https://doi.org/10.1007/s10921-021-00842-1

Published
2022
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3. Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups

Author

Beltrán, Jorge, Guindel, Carlos, de la Escalera, Arturo, and García, Fernando

Subjects
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract

Most sensor setups for onboard autonomous perception are composed of LiDARs and vision systems, as they provide complementary information that improves the reliability of the different algorithms necessary to obtain a robust scene understanding. However, the effective use of information from different sources requires an accurate calibration between the sensors involved, which usually implies a tedious and burdensome process. We present a method to calibrate the extrinsic parameters of any pair of sensors involving LiDARs, monocular or stereo cameras, of the same or different modalities. The procedure is composed of two stages: first, reference points belonging to a custom calibration target are extracted from the data provided by the sensors to be calibrated, and second, the optimal rigid transformation is found through the registration of both point sets. The proposed approach can handle devices with very different resolutions and poses, as usually found in vehicle setups. In order to assess the performance of the proposed method, a novel evaluation suite built on top of a popular simulation framework is introduced. Experiments on the synthetic environment show that our calibration algorithm significantly outperforms existing methods, whereas real data tests corroborate the results obtained in the evaluation suite. Open-source code is available at https://github.com/beltransen/velo2cam_calibration, Comment: Published on IEEE Transactions on Intelligent Transportation Systems

Published
2021
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4. Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection

Author

Kanapram, Divya Thekke, Marin-Plaza, Pablo, Marcenaro, Lucio, Martin, David, de la Escalera, Arturo, and Regazzoni, Carlo

Subjects
Computer Science - Machine Learning, Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Signal Processing
Abstract

The evolution of Intelligent Transportation Systems in recent times necessitates the development of self-awareness in agents. Before the intensive use of Machine Learning, the detection of abnormalities was manually programmed by checking every variable and creating huge nested conditions that are very difficult to track. This paper aims to introduce a novel method to develop self-awareness in autonomous vehicles that mainly focuses on detecting abnormal situations around the considered agents. Multi-sensory time-series data from the vehicles are used to develop the data-driven Dynamic Bayesian Network (DBN) models used for future state prediction and the detection of dynamic abnormalities. Moreover, an initial level collective awareness model that can perform joint anomaly detection in co-operative tasks is proposed. The GNG algorithm learns the DBN models' discrete node variables; probabilistic transition links connect the node variables. A Markov Jump Particle Filter (MJPF) is applied to predict future states and detect when the vehicle is potentially misbehaving using learned DBNs as filter parameters. In this paper, datasets from real experiments of autonomous vehicles performing various tasks used to learn and test a set of switching DBN models.

Published
2020
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5. Self-awareness in Intelligent Vehicles: Experience Based Abnormality Detection

Author

Kanapram, Divya, Marin-Plaza, Pablo, Marcenaro, Lucio, Martin, David, de la Escalera, Arturo, and Regazzoni, Carlo

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract

The evolution of Intelligent Transportation System in recent times necessitates the development of self-driving agents: the self-awareness consciousness. This paper aims to introduce a novel method to detect abnormalities based on internal cross-correlation parameters of the vehicle. Before the implementation of Machine Learning, the detection of abnormalities were manually programmed by checking every variable and creating huge nested conditions that are very difficult to track. Nowadays, it is possible to train a Dynamic Bayesian Network (DBN) model to automatically evaluate and detect when the vehicle is potentially misbehaving. In this paper, different scenarios have been set in order to train and test a switching DBN for Perimeter Monitoring Task using a semantic segmentation for the DBN model and Hellinger Distance metric for abnormality measurements., Comment: Robot 2019: Fourth Iberian Robotics Conference

Published
2020
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6. siaNMS: Non-Maximum Suppression with Siamese Networks for Multi-Camera 3D Object Detection

Author

Cortes, Irene, Beltran, Jorge, de la Escalera, Arturo, and Garcia, Fernando

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The rapid development of embedded hardware in autonomous vehicles broadens their computational capabilities, thus bringing the possibility to mount more complete sensor setups able to handle driving scenarios of higher complexity. As a result, new challenges such as multiple detections of the same object have to be addressed. In this work, a siamese network is integrated into the pipeline of a well-known 3D object detector approach to suppress duplicate proposals coming from different cameras via re-identification. Additionally, associations are exploited to enhance the 3D box regression of the object by aggregating their corresponding LiDAR frustums. The experimental evaluation on the nuScenes dataset shows that the proposed method outperforms traditional NMS approaches., Comment: Submitted to IEEE Intelligent Vehicles Symposium 2020 (IV2020)

Published
2020

7. BirdNet: a 3D Object Detection Framework from LiDAR information

Author

Beltran, Jorge, Guindel, Carlos, Moreno, Francisco Miguel, Cruzado, Daniel, Garcia, Fernando, and de la Escalera, Arturo

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Understanding driving situations regardless the conditions of the traffic scene is a cornerstone on the path towards autonomous vehicles; however, despite common sensor setups already include complementary devices such as LiDAR or radar, most of the research on perception systems has traditionally focused on computer vision. We present a LiDAR-based 3D object detection pipeline entailing three stages. First, laser information is projected into a novel cell encoding for bird's eye view projection. Later, both object location on the plane and its heading are estimated through a convolutional neural network originally designed for image processing. Finally, 3D oriented detections are computed in a post-processing phase. Experiments on KITTI dataset show that the proposed framework achieves state-of-the-art results among comparable methods. Further tests with different LiDAR sensors in real scenarios assess the multi-device capabilities of the approach., Comment: Submittied to IEEE International Conference on Intelligent Transportation Systems 2018 (ITSC)

Published
2018

9. ROS-Based Architecture for Multiple Unmanned Vehicles (UXVs) Formation

Author

Sosa San Frutos, Raúl, Al Kaff, Abdulla, Hussein, Ahmed, Madridano, Ángel, Martín, David, de la Escalera, Arturo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2020
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11. PointNet Evaluation for On-Road Object Detection Using a Multi-resolution Conditioning

Author

Pamplona, Jose, Madrigal, Carlos, de la Escalera, Arturo, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Vera-Rodriguez, Ruben, editor, Fierrez, Julian, editor, and Morales, Aythami, editor

Published
2019
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13. Complete ROS-based Architecture for Intelligent Vehicles

Author

Marin-Plaza, Pablo, Hussein, Ahmed, Martin, David, de la Escalera, Arturo, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Ollero, Anibal, editor, Sanfeliu, Alberto, editor, Montano, Luis, editor, Lau, Nuno, editor, and Cardeira, Carlos, editor

Published
2018
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14. Aerial Image Mosaicking for Multi-purpose Civil Applications

Author

Al-Kaff, Abdulla, Triviño, Juan Camilo Soto, Frutos, Raúl Sosa San, de la Escalera, Arturo, Moreno, José María Armingol, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Ollero, Anibal, editor, Sanfeliu, Alberto, editor, Montano, Luis, editor, Lau, Nuno, editor, and Cardeira, Carlos, editor

Published
2018
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18. VBII-UAV: Vision-Based Infrastructure Inspection-UAV

Author

Al-Kaff, Abdulla, Moreno, Francisco Miguel, José, Luis Javier San, García, Fernando, Martín, David, de la Escalera, Arturo, Nieva, Alberto, Garcéa, José Luis Meana, Rocha, Álvaro, editor, Correia, Ana Maria, editor, Adeli, Hojjat, editor, Reis, Luís Paulo, editor, and Costanzo, Sandra, editor

Published
2017
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19. Homography-Based Navigation System for Unmanned Aerial Vehicles

Author

Al-Kaff, Abdulla, de La Escalera, Arturo, Armingol, José María, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Penne, Rudi, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2017
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22. Neural Architectures for Feature Embedding in Person Re-Identification: A Comparative View.

Author

DOMÍNGUEZ-MARTÍN, JAVIER, GÓMEZ-SILVA, MARÍA J., and DE LA ESCALERA, ARTURO

Subjects
CONVOLUTIONAL neural networks
Abstract

Solving Person Re-Identification (Re-Id) through Deep Convolutional Neural Networks is a daunting challenge due to the small size and variety of the training data, especially in Single-Shot Re-Id, where only two images per person are available. The lack of training data causes the overfitting of the deep neural models, leading to degenerated performance. This article explores a wide assortment of neural architectures that have been commonly used for object classification and analyzes their suitability in a Re-Id model. These architectures have been trained through a Triplet Model and evaluated over two challenging Single-Shot Re-Id datasets, PRID2011 and CUHK. This comparative study is aimed at obtaining the best-performing architectures and some concluding guidance to optimize the features embedding for the Re-Identification task. The obtained results present Inception-ResNet and DenseNet as potentially useful models, especially when compared with other methods, specifically designed for solving Re-Id. [ABSTRACT FROM AUTHOR]

Published
2023
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24. SIFT and SURF Performance Evaluation and the Effect of FREAK Descriptor in the Context of Visual Odometry for Unmanned Aerial Vehicles

Author

Al-Kaff, Abdulla, de la Escalera, Arturo, Armingol, José María, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2015
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28. List of Contributors

Author

Acosta, Leopoldo, primary, Alfonso, Jorge, additional, Aliane, Nourdine, additional, Alonso, Arrate, additional, Armingol, José M., additional, Arnay, Rafael, additional, Arroyo, Roberto, additional, Artuñedo, Antonio, additional, Bergasa, Luis M., additional, Blanco, Rosa, additional, Brazález, Alfonso, additional, Cabello, Enrique, additional, Campos-Cordobés, Sergio, additional, Clavijo, Miguel, additional, de la Escalera, Arturo, additional, del Ser, Javier, additional, Fernández, Carlos, additional, Fernández, Javier, additional, Fernández, José A., additional, García, Fernando, additional, Godoy, Jorge, additional, Haber, Rodolfo, additional, Iparraguirre, Olatz, additional, Jiménez, Felipe, additional, Laña, Ibai, additional, López, Antonio M., additional, López-Lambas, Maria E., additional, Martín, David, additional, Martínez, Carlos, additional, Mata, Mario, additional, Matey, Luis, additional, Menéndez, José M., additional, Musleh, Basam, additional, Naranjo, José E., additional, Navarro, Pedro J., additional, Núñez, Borja, additional, Olabarrieta, Ignacio (Iñaki), additional, Paúl, Ana, additional, Puerta, Joshua, additional, Romera, Eduardo, additional, Sánchez, Francisco, additional, Sánchez-Cubillo, Javier, additional, Sánchez-Medina, Javier J., additional, Serrano, Ángel, additional, Toledo-Moreo, Rafael, additional, Torre-Bastida, Ana I., additional, Vázquez, David, additional, Villagra, Jorge, additional, and Villalonga, Gabriel, additional

Published
2018
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29. Positioning and Digital Maps

Author

Toledo-Moreo, Rafael, primary, Armingol, José M., additional, Clavijo, Miguel, additional, de la Escalera, Arturo, additional, Ser, Javier del, additional, Jiménez, Felipe, additional, Musleh, Basam, additional, Naranjo, José E., additional, Olabarrieta, Ignacio (Iñaki), additional, and Sánchez-Cubillo, Javier, additional

Published
2018
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36. Estimation and Prediction of the Vehicle’s Motion Based on Visual Odometry and Kalman Filter

Author

Musleh, Basam, Martin, David, de la Escalera, Arturo, Guinea, Domingo Miguel, Garcia-Alegre, Maria Carmen, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Blanc-Talon, Jacques, editor, Philips, Wilfried, editor, Popescu, Dan, editor, Scheunders, Paul, editor, and Zemčík, Pavel, editor

Published
2012
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37. U-V Disparity Analysis in Urban Environments

Author

Musleh, Basam, de la Escalera, Arturo, Armingol, José María, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2012
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40. Vehicle Detection Based on Laser Radar

Author

Garcia, Fernando, Cerri, Pietro, Broggi, Alberto, Armingol, Jose Maria, de la Escalera, Arturo, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2009
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41. Pedestrian Detection and Tracking Based on Far Infrared Visual Information

Author

Olmeda, Daniel, Hilario, Cristina, de la Escalera, Arturo, Armingol, Jose M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Bourennane, Salah, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2008
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44. Adaptative Road Lanes Detection and Classification

Author

Collado, Juan M., Hilario, Cristina, de la Escalera, Arturo, Armingol, Jose M., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Blanc-Talon, Jacques, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2006
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46. Multi-resolution Image Analysis for Vehicle Detection

Author

Hilario, Cristina, Collado, Juan Manuel, Armingol, José Maria, de la Escalera, Arturo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Marques, Jorge S., editor, Pérez de la Blanca, Nicolás, editor, and Pina, Pedro, editor

Published
2005
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