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ESPOL Polytechnic University, Ecuador

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5 Papers

Thermal Image Super-resolution: A Novel Architecture and Dataset

Authors: Rafael Rivadeneira ¹ , Angel Sappa ² and Boris Vintimilla ¹

Affiliations: ¹ Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería en Electricidad y Computación, CIDIS, Campus Gustavo Galindo, Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador , ² Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería en Electricidad y Computación, CIDIS, Campus Gustavo Galindo, Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador, Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain

Digital Object Identifier: 10.5220/0009173601110119

Quick 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 a 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 a 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.

Transfer Learning from Synthetic Data in the Camera Pose Estimation Problem

Topics: Stereo Vision and Structure from Motion; Device Calibration, Characterization and Modeling; Camera Networks and Vision

Authors: Jorge Charco ¹ , Angel Sappa ² , Boris Vintimilla ³ and Henry Velesaca ³

Affiliations: ¹ ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador, Universidad de Guayaquil, Delta and Kennedy Av., P.B. EC090514, Guayaquil, Ecuador , ² ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador, Computer Vision Center, Edifici O, Campus UAB, 08193 Bellaterra, Barcelona, Spain , ³ ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador

Digital Object Identifier: 10.5220/0009167604980505

Proceedings of VISAPP 2020, ISBN: 978-989-758-402-2

Quick 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 consists 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.

Cross-spectral Stereo Correspondence using Dense Flow Fields

Topics: Stereo Vision and Structure from Motion; Optical Flow and Motion Analyses; Vision for Robotics

Authors: Naveen Onkarappa ¹ , Cristhian A. Aguilera-Carrasco ¹ , Boris X. Vintimilla ² and Angel D. Sappa ³

Affiliations: ¹ Universitat Autònoma de Barcelona, Spain , ² Escuela Superior Politécnica del Litoral (ESPOL), Ecuador , ³ Universitat Autònoma de Barcelona and Escuela Superior Politécnica del Litoral (ESPOL), Spain

Digital Object Identifier: 10.5220/0004736006130617

Proceedings of VISAPP 2014/VISIGRAPP, ISBN: 978-989-758-009-3

Quick Abstract

This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach.

Related Ontology Subjects/Areas/Topics (8)

Applications	Optical Flow and Motion Analyses	Software Engineering
Computer Vision, Visualization and Computer Graphics	Pattern Recognition	Stereo Vision and Structure from Motion
Motion, Tracking and Stereo Vision	Robotics

Performance Evaluation of Feature Point Descriptors in the Infrared Domain

Topic: Features Extraction

Authors: Pablo Ricaurte ¹ , Carmen Chilán ¹ , Cristhian A. Aguilera-Carrasco ² , Boris X. Vintimilla ¹ and Angel D. Sappa ³

Affiliations: ¹ Escuela Superior Politénica del Litoral (ESPOL), Ecuador , ² Universitat Autònoma de Barcelona, Spain , ³ Escuela Superior Politénica del Litoral (ESPOL) and Universitat Autònoma de Barcelona, Ecuador

Digital Object Identifier: 10.5220/0004725305450550

Proceedings of VISAPP 2014/VISIGRAPP, ISBN: 978-989-758-003-1

Quick Abstract

This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered.

Related Ontology Subjects/Areas/Topics (3)

Computer Vision, Visualization and Computer Graphics

Features Extraction

Image and Video Analysis

DETECTION OF ISOLATED NEMATODES IN CLUTTER ENVIRONMENTS USING SHAPE FEATURE HISTOGRAMS

Topics: Feature Extraction; Statistical Approach; Segmentation and Grouping; Surface Geometry and Shape

Authors: Daniel Ochoa ¹ , Sidharta Gautama ¹ and Boris Vintimilla ²

Affiliations: ¹ Ghent University, Belgium , ² ESPOL University, Ecuador

Digital Object Identifier: 10.5220/0001365504860491

Proceedings of VISAPP 2006, ISBN: 972-8865-40-6

Quick Abstract

We present an approach for detection of isolated Caenohabditis Elegans nematodes in clutter environments. The method is based on shape feature histograms which describe the distribution of features of second-order derivative responses of linear image structures. The shape features are able to distinguish isolated from overlapping nematodes and clutter, thereby improving the automated image analysis of nematode populations where accurate assessment of shape is needed. An evaluation is performed on a database of manually segmented images. Shape continuity features proved to have the highest discriminative power. This is consistent with the morphological structure of this kind of organism. Our experiments suggest that similar techniques can be used for identification of other linear shaped biological objects.

Related Ontology Subjects/Areas/Topics (9)

Computer Vision, Visualization and Computer Graphics	Image and Video Analysis	Signal Processing, Sensors, Systems Modeling and Control
Feature Extraction	Informatics in Control, Automation and Robotics	Statistical Approach
Features Extraction	Segmentation and Grouping	Surface Geometry and Shape