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Author Cristhian A. Aguilera; Angel D. Sappa; Ricardo Toledo
Title Cross-Spectral Local Descriptors via Quadruplet Network Type Journal Article
Year 2017 Publication In Sensors Journal Abbreviated Journal
Volume Vol. 17 Issue Pages (down) pp. 873
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Call Number gtsi @ user @ Serial 64
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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 (down) 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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Call Number cidis @ cidis @ Serial 44
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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 Abbreviated Journal
Volume Issue Pages (down) 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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Call Number cidis @ cidis @ Serial 48
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Author Cristhian A. Aguilera; Xaver Soria; Angel D. Sappa; Ricardo Toledo
Title RGBN Multispectral Images: a Novel Color Restoration Approach Type Conference Article
Year 2017 Publication 15th International Conference on Practical Applications of Agents and Multi-Agent Systems Abbreviated Journal
Volume 619 Issue Pages (down) 155-163
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Call Number cidis @ cidis @ Serial 59
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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 (down) 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.
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Language Enlgish Summary Language English Original Title
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Call Number cidis @ cidis @ Serial 54
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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 (down)
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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Call Number cidis @ cidis @ Serial 35
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