Improving the matching of deformable objects by learning to detect keypoints

We propose a novel learned keypoint detection method to increase the number of correct matches for the task of non-rigid image correspondence. By leveraging true correspondences acquired by matching annotated image pairs with a specified descriptor extractor, we train an end-to-end convolutional neural network (CNN) to find keypoint locations that are more appropriate to the considered descriptor. For that, we apply geometric and photometric warpings to images to generate a supervisory signal, allowing the optimization of the detector. Experiments demonstrate that our method enhances the Mean Matching Accuracy of numerous descriptors when used in conjunction with our detection method, while outperforming the state-of-the-art keypoint detectors on real images of non-rigid objects by 20 p.p. We also apply our method on the complex real-world task of object retrieval where our detector performs on par with the finest keypoint detectors currently available for this task. The source code and trained models are publicly available at https://github.com/verlab/LearningToDetect_PRL_2023Comment: This is the accepted version of the paper to appear at Pattern Recognition Letters (PRL). The final journal version will be available at https://doi.org/10.1016/j.patrec.2023.08.01

Reduced caveolae density in arteries of SHR contributes to endothelial dysfunction and ROS production

Caveolae are plasma membrane invaginations enriched with high cholesterol and sphingolipid content; they also contain caveolin proteins in their structure. Endothelial nitric oxide synthase (eNOS), an enzyme that synthesizes nitric oxide (NO) by converting L-arginine to L-citrulline, is highly concentrated in plasma membrane caveolae. Hypertension is associated with decreased NO production and impaired endothelium-dependent relaxation. Understanding the molecular mechanisms that follow hypertension is important. For this study, we hypothesized that spontaneously hypertensive rat (SHR) vessels should have a smaller number of caveolae, and that the caveolae structure should be disrupted in these vessels. This should impair the eNOS function and diminish NO bioavailability. Therefore, we aimed to investigate caveolae integrity and density in SHR aortas and mesenteric arteries and the role played by caveolae in endothelium-dependent relaxation. We have been able to show the presence of caveolae-like structures in SHR aortas and mesenteric arteries. Increased phenylephrine-induced contractile response after treatment with dextrin was related to lower NO release. In addition, impaired acetylcholine-induced endothelium-dependent relaxation could be related to decreased caveolae density in SHR vessels. The most important finding of this study was that cholesterol depletion with dextrin induced eNOS phosphorylation at Serine1177 (Ser1177) and boosted reactive oxygen species (ROS) production in normotensive rat and SHR vessels, which suggested eNOS uncoupling. Dextrin plus L-NAME or BH4 decreased ROS production in aorta and mesenteric arteries supernatant's of both SHR and normotensive groups. Human umbilical vein endothelial cells (HUVECs) treated with dextrin confirmed eNOS uncoupling, as verified by the reduced eNOS dimer/monomer ratio. BH4, L-arginine, or BH4 plus L-arginine inhibited eNOS monomerization. All these results showed that caveolae structure and integrity are essential for endothelium-dependent relaxation. Additionally, a smaller number of caveolae is associated with hypertension. Finally, caveolae disruption promotes eNOS uncoupling in normotensive and hypertensive rat vessels and in HUVECs.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2016/22180-9, 2016/21239-0, 2017/14797-9]; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [400.164/2014-0, 304.137/2014-6]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

GEOBIT: A Geodesic-Based Binary Descriptor Invariant to Non-Rigid Deformations for RGB-D Images

International audienceAt the core of most three-dimensional alignment and tracking tasks resides the critical problem of point correspondence. In this context, the design of descriptors that efficiently and uniquely identifies keypoints, to be matched, is of central importance. Numerous descriptors have been developed for dealing with affine/perspective warps, but few can also handle non-rigid deformations. In this paper, we introduce a novel binary RGB-D descriptor invariant to iso-metric deformations. Our method uses geodesic isocurves on smooth textured manifolds. It combines appearance and geometric information from RGB-D images to tackle non-rigid transformations. We used our descriptor to track multiple textured depth maps and demonstrate that it produces reliable feature descriptors even in the presence of strong non-rigid deformations and depth noise. The experiments show that our descriptor outperforms different state-of-the-art descriptors in both precision-recall and recognition rate metrics. We also provide to the community a new dataset composed of annotated RGB-D images of different objects (shirts, cloths, paintings, bags), subjected to strong non-rigid deformations, to evaluate point correspondence algorithms

EXTRAÇÃO DE CONTORNO DE TELHADOS DE EDIFICAÇÕES UTILIZANDO DADOS LASER E IMAGENS AÉREAS

As tecnologias atuais para obtenção de dados geográficos estão cada vez mais precisas e possibilitam a captura de informações de uma grande área territorial em pouco tempo como, por exemplo, a varredura a laser. Outra tecnologia que já é utilizada há algum tempo é a imagem digital de alta resolução. Nesse contexto, a extração de feições a partir desses dados tem recebido, nos últimos anos, considerável atenção. Com a combinação de tipos diferentes de dados, é possível melhorar os resultados obtidos a partir da extração de objetos em cenas complexas e, por esse motivo, este trabalho desenvolveu uma ferramenta a fim de automatizar a extração do contorno dos telhados