An Improved Randomized Local Binary Features for Keypoints Recognition

Zhang, Jinming; Feng, Zuren; Zhang, Jinpeng

doi:10.3390/s18061937

Cited by 4 publications

(4 citation statements)

References 23 publications

(64 reference statements)

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“…The 3D imaging of α-SMA–stained SMCs further indicated an elongation of vessels into the peripheral lung tissue of Hx mice, but not SuHx mice, which was quantitatively evaluated by SMC elongation index ( 12 ) ( Figure 1, E and F , and Supplemental Videos 1–3 ; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.162632DS1 ). Feature-matching analysis using the AKAZE feature detector and descriptor ( 13 ) showed that the similarity score of 3D-reconstructed SMC images of SuHx against normoxia was significantly lower than that of Hx mice against normoxia ( Figure 1, G–I , and Supplemental Figure 1 ). This finding also suggests that 3D SMC remodeling is less marked in SuHx mice than in Hx mice.…”

Section: Resultsmentioning

confidence: 99%

“…Image similarity analysis by feature matching. We implemented the AKAZE algorithm (13), which is used for feature detection and description, in Python (47). Evaluating 3D images in their raw form as x-y plain images with z-stacks is difficult; therefore, we adopted a 2.5D approach, which uses 2D image representations of 3D objects (3D-reconstructed images) for feature matching, because shapes are more easily identified (48).…”

Section: Methodsmentioning

confidence: 99%

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PGC-1α–mediated angiogenesis prevents pulmonary hypertension in mice

Fujiwara,

Takeda,

Hara

et al. 2023

JCI Insight

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Pulmonary hypertension (PH) is a life-threatening disease characterized by a progressive narrowing of pulmonary arterioles. Although VEGF is highly expressed in lung of patients with PH and in animal PH models, the involvement of angiogenesis remains elusive. To clarify the pathophysiological function of angiogenesis in PH, we compared the angiogenic response in hypoxia (Hx) and SU5416 (a VEGFR2 inhibitor) plus Hx (SuHx) mouse PH models using 3D imaging. The 3D imaging analysis revealed an angiogenic response in the lung of the Hx-PH, but not of the severer SuHx-PH model. Selective VEGFR2 inhibition with cabozantinib plus Hx in mice also suppressed angiogenic response and exacerbated Hx-PH to the same extent as SuHx. Expression of endothelial proliferator-activated receptor γ coactivator 1α (PGC-1α) increased along with angiogenesis in lung of Hx-PH but not SuHx mice. In pulmonary endothelial cell–specific Ppargc1a -KO mice, the Hx-induced angiogenesis was suppressed, and PH was exacerbated along with increased oxidative stress, cellular senescence, and DNA damage. By contrast, treatment with baicalin, a flavonoid enhancing PGC-1α activity in endothelial cells, ameliorated Hx-PH with increased Vegfa expression and angiogenesis. Pulmonary endothelial PGC-1α–mediated angiogenesis is essential for adaptive responses to Hx and might represent a potential therapeutic target for PH.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

PGC-1α–mediated angiogenesis prevents pulmonary hypertension in mice

Fujiwara,

Takeda,

Hara

et al. 2023

JCI Insight

View full text Add to dashboard Cite

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“…In 2019, Ma Dan and Lai Huicheng proposed an algorithm for remote sensing image matching based on the ORB algorithm and the NSCT algorithm, which can make up for the lack of scale invariance of ORB algorithm and has more robust and comprehensive consideration in the complex situation [34]. The authors of [35] carried out researches on randomized local binary features under the background of keypoints recognition and image patches classification. They conclude that the quality of the binary feature space can be greatly improved by increasing the randomness of the basic sampling operator.…”

Section: Introductionmentioning

confidence: 99%

Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference

Xiao

et al. 2020

Sensors

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This paper presents an improved Oriented Features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) algorithm named ORB using three-patch and local gray difference (ORB-TPLGD). ORB takes a breakthrough in real-time aspect. However, subtle changes of the image may greatly affect its final binary description. In this paper, the feature description generation is focused. On one hand, instead of pixel patch pairs comparison method used in present ORB algorithm, a three-pixel patch group comparison method is adopted to generate the binary string. In each group, the gray value of the main patch is compared with that of the other two companion patches to determine the corresponding bit of the binary description. On the other hand, the present ORB algorithm simply uses the gray size comparison between pixel patch pairs, while ignoring the information of the gray difference value. In this paper, another binary string based on the gray difference information mentioned above is generated. Finally, the feature fusion method is adopted to combine the binary strings generated in the above two steps to generate a new feature description. Experiment results indicate that our improved ORB algorithm can achieve greater performance than ORB and some other related algorithms.

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“…Dominik Belter et al [17] investigate the influence of the uncertainty models of point features on the accuracy of the estimated trajectory and map in more detail and propose mathematical uncertainty models for point features in RGB-D SLAM. Unlike research on filtering strategies, Jinming Zhang et al [18] carry out researches on randomized local binary features and propose using more general randomized intensity difference sampling operator to construct binary feature space for keypoints recognition. Qinghua Yu et al [19] propose a novel perspective invariant feature transform (PIFT) for RGBD images.…”

Section: Introductionmentioning

confidence: 99%

EF-Razor: An Effective Edge-Feature Processing Method in Visual SLAM

Liu

Jiao

et al. 2020

IEEE Access

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Feature-based visual simultaneous localization and mapping (SLAM) is an effective localization approach for robots in unknown environments. Classic handcrafted features perform well in 2D image matching tasks. However, in the tracking task of SLAM, the region at the edge of the object in the image is often unstable because of the lack of spatial information. In this paper, we refer to the features at the edge of the object as edge-features and propose an effective method to process the edge-features in SLAM named Edge-Feature Razor (EF-Razor) for the above problems. EF-Razor first uses the semantics provided by the object detection YOLOv3 to distinguish edge-features. Through additional constraints on edgefeatures matching in the tracking process, EF-Razor can effectively reduce the impact of unstable features on the SLAM system. Then, EF-Razor adjusts the information matrix to increase the system's trust in the filtered features. This will make the calculation result of the bundle adjustment more stable. In order to evaluate the proposed method, we integrate EF-Razor to ORB-SLAM2 and perform experiments. The comparison results based on public datasets show the proposed method could effectively reduce the absolute trajectory error by 7%. INDEX TERMS edge, features, object detection, simultaneous localization and mapping.

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An Improved Randomized Local Binary Features for Keypoints Recognition

Cited by 4 publications

References 23 publications

PGC-1α–mediated angiogenesis prevents pulmonary hypertension in mice

PGC-1α–mediated angiogenesis prevents pulmonary hypertension in mice

Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference

EF-Razor: An Effective Edge-Feature Processing Method in Visual SLAM

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