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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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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 44 | ||
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| Author | Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla | ||||
| 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 | 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 | |
| Volume | 331 | Issue | Pages | ||
| 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 | Editor | |
| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 35 | ||
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| Author | Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla | ||||
| Title | An approach to automatic assistance in physiotherapy based on on-line movement identification. | Type | Conference Article | ||
| Year | 2012 | Publication | VI Andean Region International Conference – ANDESCON 2012 | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords |
patient rehabilitation, patient treatment, statistical analysis | ||||
| Abstract | This paper describes a method for on-line movement identification, oriented to patient’s movement evaluation during physiotherapy. An analysis based on Mahalanobis distance between temporal windows is performed to identify the “idle/motion” state, which defines the beginning and end of the patient’s movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments. | ||||
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| Publisher | IEEE | Place of Publication | Andean Region International Conference (ANDESCON), 2012 VI | Editor | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 24 | ||
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| Author | Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla | ||||
| Title | Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. | Type | Journal Article | ||
| Year | 2015 | Publication | Revista Tecnológica ESPOL-RTE | Abbreviated Journal | |
| Volume | Vol. 28 | Issue | Pages | pp. 1-7 | |
| Keywords |
Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb | ||||
| Abstract | Comúnmente durante la rehabilitación física, el diagnóstico dado por el especialista se basa en observaciones cualitativas que sugieren, en algunos casos, conclusiones subjetivas. El presente trabajo propone un enfoque cuantitativo, orientado a servir de ayuda a fisioterapeutas, a través de una herramienta interactiva y de bajo costo que permite medir los movimientos de miembros superiores. Estos movimientos son capturados por un sensor RGB-D y procesados mediante la metodología propuesta, dando como resultado una eficiente representación de movimientos, permitiendo la evaluación cuantitativa de movimientos de los miembros superiores. | ||||
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| Publisher | ESPOL | Place of Publication | Editor | ||
| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 39 | ||
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| Author | Jorge L. Charco; Angel D. Sappa; Boris X. Vintimilla; Henry O. Velesaca | ||||
| 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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| ISSN | ISBN | 978-989758402-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 120 | ||
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| Author | Rafael E. Rivadeneira; Angel D. Sappa; Boris X. Vintimilla | ||||
| Title | Thermal Image Super-Resolution: a Novel Architecture and Dataset | 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 | 111-119 | |
| Keywords |
Thermal images, Far Infrared, Dataset, Super-Resolution. | ||||
| Abstract | This paper proposes a novel CycleGAN architecture for thermal image super-resolution, together with a large dataset consisting of thermal images at different resolutions. The dataset has been acquired using three thermal cameras at different resolutions, which acquire images from the same scenario at the same time. The thermal cameras are mounted in rig trying to minimize the baseline distance to make easier the registration problem. The proposed architecture is based on ResNet6 as a Generator and PatchGAN as Discriminator. The novelty on the proposed unsupervised super-resolution training (CycleGAN) is possible due to the existence of aforementioned thermal images—images of the same scenario with different resolutions. The proposed approach is evaluated in the dataset and compared with classical bicubic interpolation. The dataset and the network are available. |
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| ISSN | ISBN | 978-989758402-2 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 121 | ||
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