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	Author	Kevin E. Muñoz Loberlly N. Salazar Steven S. Araujo Boris X. Vintimilla
	Title	Detecting and Characterizing Human Interactions to EnhanceHuman-Robot Engagement			Type	Conference Article
	Year	2025	Publication	3rd International Conference on Robotics, Control and Vision Engineering RCVE 2025	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	281
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	Author	Marjorie Chalen; Boris X. Vintimilla
	Title	Towards Action Prediction Applying Deep Learning			Type	Journal Article
	Year	2019	Publication	Latin American Conference on Computational Intelligence (LA-CCI); Guayaquil, Ecuador; 11-15 Noviembre 2019	Abbreviated Journal
	Volume		Issue		Pages	pp. 1-3
	Keywords	action prediction, early recognition, early detec- tion, action anticipation, cnn, deep learning, rnn, lstm.
	Abstract	Considering the incremental development future action prediction by video analysis task of computer vision where it is done based upon incomplete action executions. Deep learning is playing an important role in this task framework. Thus, this paper describes recently techniques and pertinent datasets utilized in human action prediction task.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	129
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	Author	Ricaurte P; Chilán C; Cristhian A. Aguilera; Boris X. Vintimilla; Angel D. Sappa
	Title	Feature Point Descriptors: Infrared and Visible Spectra			Type	Journal Article
	Year	2014	Publication	Sensors Journal	Abbreviated Journal
	Volume	Vol. 14	Issue		Pages	pp. 3690-3701
	Keywords	cross-spectral imaging; feature point descriptors
	Abstract	This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	28
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	Author	Patricia L. Suárez, Angel D. Sappa, Boris X. Vintimilla
	Title	Cycle generative adversarial network: towards a low-cost vegetation index estimation			Type	Conference Article
	Year	2021	Publication	IEEE International Conference on Image Processing (ICIP 2021)	Abbreviated Journal
	Volume	2021-September	Issue		Pages	2783-2787
	Keywords	CyclicGAN, NDVI, near infrared spectra, instance normalization.
	Abstract	This paper presents a novel unsupervised approach to estimate the Normalized Difference Vegetation Index (NDVI).The NDVI is obtained as the ratio between information from the visible and near infrared spectral bands; in the current work, the NDVI is estimated just from an image of the visible spectrum through a Cyclic Generative Adversarial Network (CyclicGAN). This unsupervised architecture learns to estimate the NDVI index by means of an image translation between the red channel of a given RGB image and the NDVI unpaired index’s image. The translation is obtained by means of a ResNET architecture and a multiple loss function. Experimental results obtained with this unsupervised scheme show the validity of the implemented model. Additionally, comparisons with the state of the art approaches are provided showing improvements with the proposed approach.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	164
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	Author	Dennis G. Romero; A. Frizera; Angel D. Sappa; Boris X. Vintimilla; T.F. Bastos
	Title	A predictive model for human activity recognition by observing actions and context			Type	Conference Article
	Year	2015	Publication	ACIVS 2015 (Advanced Concepts for Intelligent Vision Systems), International Conference on, Catania, Italy, 2015	Abbreviated Journal
	Volume		Issue		Pages	323 - 333
	Keywords	Edge width, Image blu,r Defocus map, Edge model
	Abstract	This paper presents a novel model to estimate human activities – a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	43
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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)	Abbreviated Journal
	Volume	Vol. 4	Issue		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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	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	Abbreviated Journal
	Volume		Issue		Pages	1-6
	Keywords	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	52
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	Author	Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla
	Title	RWE patterns extraction for on-line human action recognition through window-based analysis of invariant moments			Type	Conference Article
	Year	2012	Publication	5th Workshop in applied Robotics and Automation (RoboControl)	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Human action recognition, Relative Wavelet Energy, Window-based temporal analysis.
	Abstract	This paper presents a method for on-line human action recognition on video sequences. An analysis based on Mahalanobis distance is performed to identify the “idle” state, which defines the beginning and end of the person movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	23
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	Author	Angel D. Sappa; Juan A. Carvajal; Cristhian A. Aguilera; Miguel Oliveira; Dennis G. Romero; Boris X. Vintimilla
	Title	Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study			Type	Journal Article
	Year	2016	Publication	Sensors Journal	Abbreviated Journal
	Volume	Vol. 16	Issue		Pages	pp. 1-15
	Keywords	image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform
	Abstract	This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and LongWave InfraRed (LWIR).
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	47
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	Author	Angel D. Sappa; Cristhian A. Aguilera; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo
	Title	Monocular visual odometry: a cross-spectral image fusion based approach			Type	Journal Article
	Year	2016	Publication	Robotics and Autonomous Systems Journal	Abbreviated Journal
	Volume	Vol. 86	Issue		Pages	pp. 26-36
	Keywords	Monocular visual odometry LWIR-RGB cross-spectral imaging Image fusion
	Abstract	This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is em- pirically obtained by means of a mutual information based evaluation met- ric. The objective is to have a exible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odom- etry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	Enlgish	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	cidis @ cidis @			Serial	54
Permanent link to this record