| Records |
| Author |
Mildred Cruz; Cristhian A. Aguilera; Boris X. Vintimilla; Ricardo Toledo; Ángel D. Sappa |
| Title |
Cross-spectral image registration and fusion: an evaluation study |
Type |
Conference Article |
| Year |
2015 |
Publication |
2nd International Conference on Machine Vision and Machine Learning |
Abbreviated Journal |
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| Volume |
331 |
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| Keywords |
multispectral imaging; image registration; data fusion; infrared and visible spectra |
| Abstract |
This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented. |
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| Publisher |
Computer Vision Center |
Place of Publication |
Barcelona, Spain |
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English |
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English |
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no |
| Call Number |
cidis @ cidis @ |
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35 |
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| Author |
Miguel Realpe; Boris X. Vintimilla; L. Vlacic |
| Title |
Towards Fault Tolerant Perception for autonomous vehicles: Local Fusion. |
Type |
Conference Article |
| Year |
2015 |
Publication |
IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Siem Reap, 2015. |
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253-258 |
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| Abstract |
Many robust sensor fusion strategies have been developed in order to reliably detect the surrounding environments of an autonomous vehicle. However, in real situations there is always the possibility that sensors or other components may fail. Thus, internal modules and sensors need to be monitored to ensure their proper function. This paper introduces a general view of a perception architecture designed to detect and classify obstacles in an autonomous vehicle's environment using a fault tolerant framework, whereas elaborates the object detection and local fusion modules proposed in order to achieve the modularity and real-time process required by the system. |
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no |
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cidis @ cidis @ |
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37 |
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| Author |
Dennys Paillacho; Cecilio Angulo; Marta Díaz. |
| Title |
An Exploratory Study of Group-Robot Social Interactions in a Cultural Center |
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Conference Article |
| Year |
2015 |
Publication |
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015, International Conference on, Hamburg, Germany, 2015 |
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This article describes an exploratory study of social human-robot interaction with the experimental robotic platform MASHI. The experiences were carried out in La B`obila Cultural Center in Barcelona, Spain to study the visitor preferences, characterize the groups and their spatial relationships in this open and unstructured environment. Results showed that visitors prefers to play and dialogue with the robot. Children have the highest interest in interacting with the robot, more than young and adult visitors. Most of the groups consisted of more than 3 visitors, however the size of the groups during interactions was continuously changed. In static situations, the observed spatial relationships denotes a social cohesion in the human-robot interactions. |
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no |
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gtsi @ user @ |
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67 |
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| Author |
Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias |
| Title |
Scene representations for autonomous driving: an approach based on polygonal primitives |
Type |
Conference Article |
| Year |
2015 |
Publication |
Iberian Robotics Conference (ROBOT 2015), Lisbon, Portugal, 2015 |
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| Volume |
417 |
Issue |
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Pages |
503-515 |
| Keywords |
Scene reconstruction, Point cloud, Autonomous vehicles |
| Abstract |
In this paper, we present a novel methodology to compute a 3D scene representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques. |
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Springer International Publishing Switzerland 2016 |
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English |
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English |
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Second Iberian Robotics Conference |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
45 |
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| Author |
Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo |
| Title |
Learning crossspectral similarity measures with deep convolutional neural networks |
Type |
Conference Article |
| Year |
2016 |
Publication |
IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops |
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Pages |
267-275 |
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| Abstract |
The simultaneous use of images from different spectra can be helpful to improve the performance of many com- puter vision tasks. The core idea behind the usage of cross- spectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN archi- tectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Ex- perimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Ad- ditionally, our experiments show that some CNN architec- tures are capable of generalizing between different cross- spectral domains. |
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English |
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no |
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cidis @ cidis @ |
Serial |
48 |
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| Author |
Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic |
| Title |
Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles |
Type |
Journal Article |
| Year |
2016 |
Publication |
Journal of Automation and Control Engineering (JOACE) |
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| Volume |
Vol. 4 |
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Pages |
pp. 430-436 |
| Keywords |
Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System |
| Abstract |
Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset. |
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English |
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Approved |
no |
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cidis @ cidis @ |
Serial |
51 |
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| Author |
Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic |
| Title |
A Fault Tolerant Perception system for autonomous vehicles |
Type |
Conference Article |
| Year |
2016 |
Publication |
35th Chinese Control Conference (CCC2016), International Conference on, Chengdu |
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Pages |
1-6 |
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Fault Tolerant Perception, Sensor Data Fusion, Fault Tolerance, Autonomous Vehicles, Federated Architecture |
| Abstract |
Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset. |
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English |
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no |
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cidis @ cidis @ |
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52 |
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| Author |
Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa |
| Title |
Fine-tuning based deep covolutional networks for lepidopterous genus recognition |
Type |
Conference Article |
| Year |
2016 |
Publication |
XXI IberoAmerican Congress on Pattern Recognition |
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1-9 |
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This paper describes an image classi cation approach ori- ented to identify specimens of lepidopterous insects recognized at Ecuado- rian ecological reserves. This work seeks to contribute to studies in the area of biology about genus of butter ies and also to facilitate the reg- istration of unrecognized specimens. The proposed approach is based on the ne-tuning of three widely used pre-trained Convolutional Neural Networks (CNNs). This strategy is intended to overcome the reduced number of labeled images. Experimental results with a dataset labeled by expert biologists, is presented|a recognition accuracy above 92% is reached. 1 Introductio |
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no |
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cidis @ cidis @ |
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53 |
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| Author |
Angely Oyola; Dennis G. Romero; Boris X. Vintimilla |
| Title |
A Dijkstra-based algorithm for selecting the Shortest-Safe Evacuation Routes in dynamic environments (SSER) |
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Conference Article |
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2017 |
Publication |
The 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017) |
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131-135 |
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cidis @ cidis @ |
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55 |
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| Author |
Sianna Puente; Cindy Madrid; Miguel Realpe; Boris X. Vintimilla |
| Title |
An Empirical Comparison of DCNN libraries to implement the Vision Module of a Danger Management System |
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Conference Article |
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2017 |
Publication |
2017 International Conference on Deep Learning Technologies (ICDLT 2017) |
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Part F128535 |
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60-65 |
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cidis @ cidis @ |
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56 |
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