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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Adaptive Harris Corners Detector Evaluated with Cross-Spectral Images | Type | Conference Article | ||
| Year | 2018 | Publication | International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing | Abbreviated Journal | |
| Volume | 721 | Issue | Pages | ||
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| Abstract | This paper proposes a novel approach to use cross-spectral images to achieve a better performance with the proposed Adaptive Harris corner detector comparing its obtained results with those achieved with images of the visible spectra. The images of urban, field, old-building and country category were used for the experiments, given the variety of the textures present in these images, with which the complexity of the proposal is much more challenging for its verification. It is a new scope, which means improving the detection of characteristic points using crossspectral images (NIR, G, B) and applying pruning techniques, the combination of channels for this fusion is the one that generates the largest variance based on the intensity of the merged pixels, therefore, it is that which maximizes the entropy in the resulting Cross-spectral images. Harris is one of the most widely used corner detection algorithm, so any improvement in its efficiency is an important contribution in the field of computer vision. The experiments conclude that the inclusion of a (NIR) channel in the image as a result of the combination of the spectra, greatly improves the corner detection due to better entropy of the resulting image after the fusion, Therefore the fusion process applied to the images improves the results obtained in subsequent processes such as identification of objects or patterns, classification and/or segmentation. |
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| Notes | 1 | Approved | no | ||
| Call Number | gtsi @ user @ | Serial | 84 | ||
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| Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Cross-spectral image dehaze through a dense stacked conditional GAN based approach. | Type | Conference Article | ||
| Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet based Systems (SITIS 2018) | Abbreviated Journal | |
| Volume | Issue | Pages | 358-364 | ||
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| Abstract | This paper proposes a novel approach to remove haze from RGB images using a near infrared images based on a dense stacked conditional Generative Adversarial Network (CGAN). The architecture of the deep network implemented receives, besides the images with haze, its corresponding image in the near infrared spectrum, which serve to accelerate the learning process of the details of the characteristics of the images. The model uses a triplet layer that allows the independence learning of each channel of the visible spectrum image to remove the haze on each color channel separately. A multiple loss function scheme is proposed, which ensures balanced learning between the colors and the structure of the images. Experimental results have shown that the proposed method effectively removes the haze from the images. Additionally, the proposed approach is compared with a state of the art approach showing better results. | ||||
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| Call Number | gtsi @ user @ | Serial | 92 | ||
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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 | |
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| 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. | ||||
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| Language | English | Summary Language | English | Original Title | |
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| Call Number | cidis @ cidis @ | Serial | 23 | ||
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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. | ||||
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| Call Number | cidis @ cidis @ | Serial | 28 | ||
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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. | Abbreviated Journal | |
| Volume | Issue | Pages | 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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| Call Number | cidis @ cidis @ | Serial | 37 | ||
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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. | ||||
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| Call Number | cidis @ cidis @ | Serial | 43 | ||
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| Author | Julien Poujol; Cristhian A. Aguilera; Etienne Danos; Boris X. Vintimilla; Ricardo Toledo; Angel D. Sappa | ||||
| 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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| Call Number | cidis @ cidis @ | Serial | 44 | ||
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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). | ||||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 47 | ||
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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. | ||||
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| 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. | ||||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 52 | ||
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