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Author (up) Jorge Alvarez Tello; Mireya Zapata; Dennys Paillacho pdf  openurl
  Title Kinematic optimization of a robot head movements for the evaluation of human-robot interaction in social robotics. Type Conference Article
  Year 2019 Publication 10th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences (AHFE 2019), Washington D.C.; United States. Advances in Intelligent Systems and Computing Abbreviated Journal  
  Volume 975 Issue Pages 108-118  
  Keywords  
  Abstract This paper presents the simplification of the head movements from

the analysis of the biomechanical parameters of the head and neck at the

mechanical and structural level through CAD modeling and construction with

additive printing in ABS/PLA to implement non-verbal communication strategies and establish behavior patterns in the social interaction. This is using in the

denominated MASHI (Multipurpose Assistant robot for Social Human-robot

Interaction) experimental robotic telepresence platform, implemented by a

display with a fish-eye camera along with the mechanical mechanism, which

permits 4 degrees of freedom (DoF). In the development of mathematicalmechanical modeling for the kinematics codification that governs the robot and

the autonomy of movement, we have the Pitch, Roll, and Yaw movements, and

the combination of all of them to establish an active communication through

telepresence. For the computational implementation, it will be show the rotational matrix to describe the movement.		  
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  Notes Approved yes  
  Call Number gtsi @ user @ Serial 108  
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Author (up) Jorge Alvarez; Mireya Zapata; Dennys Paillacho pdf  openurl
  Title Mechanical Design of a spatial mechanism for the robot head movements in social robotics for the evaluation of Human-Robot Interaction. Type Conference Article
  Year 2019 Publication 2nd International Conference on Human Systems Engineering and Design: Future Trends and Applications (IHSED 2019); Munich, Alemania Abbreviated Journal  
  Volume 1026 Issue Pages 160-165  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 104  
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Author (up) Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla pdf  openurl
  Title Human Pose Estimation through A Novel Multi-View Scheme Type Conference Article
  Year 2022 Publication Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 Abbreviated Journal  
  Volume 5 Issue Pages 855-862  
  Keywords Multi-View Scheme, Human Pose Estimation, Relative Camera Pose, Monocular Approach  
  Abstract This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human

pose estimation problem. The proposed approach first obtains the human body joints of a set of images,

which are captured from different views at the same time. Then, it enhances the obtained joints by using a

multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from

another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed

for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and

comparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements

in the accuracy of body joints estimations.		  
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  Notes Approved yes  
  Call Number cidis @ cidis @ Serial 169  
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Author (up) Jorge L. Charco; Angel D. Sappa; Boris X. Vintimilla; Henry O. Velesaca pdf  isbn
openurl 
  Title Transfer Learning from Synthetic Data in the Camera Pose Estimation Problem Type Conference Article
  Year 2020 Publication The 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020); Valletta, Malta; 27-29 Febrero 2020 Abbreviated Journal  
  Volume 4 Issue Pages 498-505  
  Keywords Relative Camera Pose Estimation, Siamese Architecture, Synthetic Data, Deep Learning, Multi-View Environments, Extrinsic Camera Parameters.  
  Abstract This paper presents a novel Siamese network architecture, as a variant of Resnet-50, to estimate the relative camera pose on multi-view environments. In order to improve the performance of the proposed model

a transfer learning strategy, based on synthetic images obtained from a virtual-world, is considered. The

transfer learning consist of first training the network using pairs of images from the virtual-world scenario

considering different conditions (i.e., weather, illumination, objects, buildings, etc.); then, the learned weight

of the network are transferred to the real case, where images from real-world scenarios are considered. Experimental results and comparisons with the state of the art show both, improvements on the relative pose

estimation accuracy using the proposed model, as well as further improvements when the transfer learning

strategy (synthetic-world data – transfer learning – real-world data) is considered to tackle the limitation on

the training due to the reduced number of pairs of real-images on most of the public data sets.		  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989758402-2 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 120  
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Author (up) Jorge L. Charco; Boris X. Vintimilla; Angel D. Sappa pdf  openurl
  Title Deep learning based camera pose estimation in multi-view environment. Type Conference Article
  Year 2018 Publication 14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) Abbreviated Journal  
  Volume Issue Pages 224-228  
  Keywords  
  Abstract This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from scratch on a large data set that takes as input a pair of images from the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose.  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 93  
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Author (up) José Reyes; Axel Godoy; Miguel Realpe. pdf  openurl
  Title Uso de software de código abierto para fusión de imágenes agrícolas multiespectrales adquiridas con drones. Type Conference Article
  Year 2019 Publication International Multi-Conference of Engineering, Education and Technology (LACCEI 2019); Montego Bay, Jamaica Abbreviated Journal  
  Volume 2019-July Issue Pages  
  Keywords  
  Abstract Los drones o aeronaves no tripuladas son muy útiles para la adquisición de imágenes, de forma mucho más simple que los satélites o aviones. Sin embargo, las imágenes adquiridas por drones deben ser combinadas de alguna forma para convertirse en información de valor sobre un terreno o cultivo. Existen diferentes programas que reciben imágenes y las combinan en una sola imagen, cada uno con diferentes características (rendimiento, precisión, resultados, precio, etc.). En este estudio se revisaron diferentes programas de código abierto para fusión de imágenes, con el ?n de establecer cuál de ellos es más útil, especí?camente para ser utilizado por pequeños y medianos agricultores en Ecuador. Los resultados pueden ser de interés para diseñadores de software, ya que al utilizar código abierto, es posible modi?car e integrar los programas en un ?ujo de trabajo más simpli?cado. Además, que permite disminuir costos debido a que no requiere de pagos de licencias para su uso, lo cual puede repercutir en un mayor acceso a la tecnología para los pequeños y medianos agricultores. Como parte de los resultados de este estudio se ha creado un repositorio de acceso público con algoritmos de pre-procesamiento necesarios para manipular las imágenes adquiridas por una cámara multiespectral y para luego obtener un mapa completo en formatos RGB, CIR y NDVI.  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 102  
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Author (up) Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa pdf  openurl
  Title Fine-tuning based deep covolutional networks for lepidopterous genus recognition Type Conference Article
  Year 2016 Publication XXI IberoAmerican Congress on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1-9  
  Keywords  
  Abstract 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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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 53  
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Author (up) Juan C. Basurto, Patricia Chávez and Hernán Córdova pdf  openurl
  Title A Proximity-Aware Transparent Handoff Mobility Scheme for VoIP Communication over Infrastructure Mesh Networks Type Conference Article
  Year 2011 Publication International Congress of Electronic, Electrical and Systems Engineering-INTERCON 2011 Abbreviated Journal  
  Volume Issue Pages  
  Keywords Wireless Mesh Networks; Quality of Service; Mobility Management; Voice over IP.  
  Abstract Mobility Management plays a key role in Voice-over- IP (VoIP) communications over Wireless Mesh Networks (WMN) as clients should maintain adequate levels of Quality of Service (QoS) as they move across the network. This paper presents PATH, a Proximity-Aware Transparent Handoff mobility scheme for real time voice communications over wireless mesh networks. Our study focuses on Medium Access Control (MAC) layer procedures and relies on gratuitous ARP unicasting in order to provide fast-handoffs. An experimental evaluation has been conducted and its results are shown in this paper.  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 20  
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Author (up) Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa pdf  url
openurl 
  Title A visible-Thermal Fusion based Monocular Visual Odometry Type Conference Article
  Year 2015 Publication Iberian Robotics Conference (ROBOT 2015), International Conference on, Lisbon, Portugal, 2015 Abbreviated Journal  
  Volume 417 Issue Pages 517-528  
  Keywords Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion  
  Abstract The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained representations are evaluated under a visual odometry framework, highlighting their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach.  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 44  
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Author (up) Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. pdf  url
openurl 
  Title Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. Type Conference Article
  Year 2022 Publication Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. Abbreviated Journal CONFERENCE  
  Volume 2022-June Issue Pages 417-425  
  Keywords  
  Abstract This paper details the results and main findings of the

second iteration of the Multi-modal Aerial View Object

Classification (MAVOC) challenge. This year’s MAVOC

challenge is the second iteration. The primary goal of

both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) input

modalities. Teams are encouraged/challenged to develop

multi-modal approaches that incorporate complementary

information from both domains. While the 2021 challenge

showed a proof of concept that both modalities could be

used together, the 2022 challenge focuses on the detailed

multi-modal models. Using the same UNIfied COincident

Optical and Radar for recognitioN (UNICORN) dataset and

competition format that was used in 2021. Specifically, the

challenge focuses on two techniques, (1) SAR classification

and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods

and describing their performance on our blind test set. Notably, all of the top ten teams outperform our baseline. For

SAR classification, the top team showed a 129% improvement over our baseline and an 8% average improvement

from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average

improvement over 2021.		  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 177  
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