Zhan Song

Wenzhou Medical University

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Yuping Ye

Shenzhen Institutes of Advanced Technology

Feifei Gu

Shenzhen Institutes of Advanced Technology

Feng Zheng

Southern University of Science and Technology

Suming Tang

China Medical University

Juan Zhao

Shenzhen Institutes of Advanced Technology

Jixin Liang

Chinese Academy of Sciences

Yanguo Zhao

Hebei Medical University

Ronald Chung

Chinese University of Hong Kong

Ling Shao

University of Chinese Academy of Sciences

Qingsong Zhu

State Grid Corporation of China (China)

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Chinese Academy of Sciences

119

Shenzhen Institutes of Advanced Technology

University of Chinese Academy of Sciences

Chinese University of Hong Kong

Zhejiang University

University of Hong Kong

Tsinghua University

Huazhong University of Science and Technology

Xidian University

Chinese University of Hong Kong, Shenzhen

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Key airworthiness validation technologies for icing of general aviation aircraft and their engineering application

Hangkong Xuebao (2016)

Hongwei Wang Li Xianzhe Zhan Song

Airworthiness

Aviation safety

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A Robust Pose Optimization Scheme With Spatial Geometry Awareness for Hybrid Bronchoscopic Navigation

IEEE Transactions on Instrumentation and Measurement (2024)

Hao Liu Zhang Sheng-lin Yongming Yang Lei Sun Zhan Song

Interventional bronchoscopy is a minimally invasive procedure used to diagnose and treat peripheral pulmonary nodules. Bronchoscope navigation is one of the crucial technologies for guiding the biopsy pose with precision. However, electromagnetic navigation is vulnerable to respiratory motion and tissue displacement, while visual navigation of continuous frames can become unstable in blurred scenes. To overcome these challenges, we propose a robust two-stage hybrid navigation framework that integrates spatial geometry awareness with hybrid update block. Our spatial-aware network leverages the strength of normal and gradient losses to deal with small structural fluctuations and stepped edges. It is trained on a synthetic scenario dataset and can be generalized to in-vivo scenes. Using the initial pose from electromagnetic keypoint registration, a hybrid update block employs the spatial-aware network as a reliable and content-rich feature comparator to perform efficient optimal pose search with swarm intelligence. Positional and orientational accuracy of our method has been verified and compared with recent SOTA methods in phantom and animal experiments. Both quantitative and qualitative results demonstrate that we provide a promising method for improving the accuracy and robustness of bronchoscopic navigation.

10.1109/tim.2024.3376689

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Recent advances and trends in visual tracking: A review

Neurocomputing (2011)

Hanxuan Yang Ling Shao Feng Zheng Liang Wang Zhan Song

Tracking (education)

Feature (linguistics)

10.1016/j.neucom.2011.07.024

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Citations (600)

Whitening central projection descriptor for affine‐invariant shape description

IET Image Processing (2013)

Rushi Lan Jianwei Yang Yong Jiang Colin Fyfe Zhan Song

A novel descriptor, referred to as the whitening central projection predictor (WCPD), is developed for affine‐invariant shape description. The proposed descriptor is based on central projection transform (CPT) and whitening transform (WT). Dislike contour‐based or region‐based approaches, an object is first converted to a closed curve by CPT, which is called the general curve (GC). The derived GC not only keeps the affine transform information, but also is very robust to noise. Then WT is performed to the GC with the purpose that the affine transformation is simplified to a rotation only. Finally, Fourier descriptors are employed to remove the rotation, and WCPD is obtained. One advantage of using WCPD for affine‐invariant description lies in that it is applicable to objects consisting of several components. Furthermore, the approach used on the GC is contour‐based, and is of small computational complexity. Several experiments have been conducted to evaluate the performance of the proposed method. Experimental results show that the proposed method has a powerful discrimination ability, and is more robust to noise.

10.1049/iet-ipr.2012.0094

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Citations (9)

SGVM: Semantic-Guided Variational Model for Sealing Nail Defect Extraction Within Albedo Domain via Photometric Stereo

IEEE Access (2023)

Fang Liu Wei Cao Yuping Ye Feifei Gu Shiyang Long

Automatic 2D vision-based defect detection on sealing nail (SealN) surfaces is challenging due to interference of complex backgrounds with non-homogeneous and low contrast between foreground and background. Inspired by an interesting observation that the albedo domain recovered by the uncalibrated photometric stereo (UPS) shows obvious differences and significant abruptness between defects’ and non-defects’ regions, we develop a novel semantic-guided variational model (SGVM) to conditional extract structural defects from albedo map. Specifically, SGVM utilizes one developed global regularized label indicator to semantically guide one local regularized relative Gaussian filter (RGF) for achieving large-scale structures (i.e., defects) preservation and small-scale textures (i.e., background) suppression. Furthermore, defects can be efficiently extracted by thresholding the structure map within the label indicator. Additionally, experimental results on numerous challenging defect images reveal that the proposed SGVM outperforms the existing advanced 2D methods in terms of defect extraction.

Albedo (alchemy)

Gaussian filter

10.1109/access.2023.3329116

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CSIE: Coded strip-patterns image enhancer embedded in structured light-based methods

Optics and Lasers in Engineering (2023)

Wei Cao Ruiping Wang Yuping Ye Chu Shi Zhan Song

Visibility

Smoothness

10.1016/j.optlaseng.2023.107561

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Citations (2)

An affine invariant discriminate analysis with canonical correlation analysis

Neurocomputing (2012)

Rushi Lan Jianwei Yang Yong Jiang Zhan Song Yuan Yan Tang

Canonical correlation

Canonical analysis

10.1016/j.neucom.2012.01.026

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Citations (9)

Robust Feature Detection Method in High-density Structured Light System

Feifei Gu Jianyang Feng Pengju Xie Huazhao Cao Zhan Song

How to achieve high coding density with a small coding window by using a few coding elements is an interesting and challenging topic in the research domain of structured light techniques (SLT). This paper designed a high-density coding pattern in SLT and a corresponding subpixel feature detection algorithm was proposed. The pattern primitives were designed as checkerboard blocks with a simple embedded geometrical shape - L. Two different types of features are involved to guarantee high coding density. One is checkerboard grid points, which were taken as the main features (MFs) and the other is L shape feature points, which were taken as the auxiliary features (AFs). Specially-designed templates were utilized to locate MFs and a robust feature detecting method based on K-means clustering and Shi-Tomasi algorithm were utilized to locate the AFs accurately. With both MFs and AFs, the density of reconstructed point clouds can be increased by threefold.

Feature (linguistics)

10.1145/3374587.3374618

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Citations (3)

An Accurate Phase Measuring Deflectometry Method for 3D Reconstruction of Mirror-Like Specular Surface

Hao Han Shiqian Wu Zhan Song Juan Zhao

Measurement of specular surface shape is still a challenging task for existing 3D scanning techniques. In this paper, an accurate phase measuring deflectometry method is investigated for 3D reconstruction of mirror surfaces. To calibrate the system parameters, a standard flat mirror is used. By the reflected checkerboard pattern displayed by the LCD screen, the camera intrinsic parameters are calibrated firstly. The last orientation of calibration mirror is aligned as the reference plane. With such a calibration manner, intrinsic camera parameters, lens distortion and the LCD position can be determined efficiently. By displaying both horizontal and vertical Gray code plus sinusoidal shifting patterns on the LCD screen, dense surface gradient field is calculated with the proposed slope calculation method, and then integrated to retrieve precise 3D surface shapes. The experiments conducted with both flat and concave mirror surface demonstrate that high precision measurement results can be obtained.

Surface reconstruction

Phase Unwrapping

Surface fitting

10.1109/icoias.2019.00010

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Citations (3)

Miniature 3D Depth Camera for Real-time Reconstruction

2021 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2019)

Zi-Long Zhao Feifei Gu Pengju Xie Huazhao Cao Zhan Song

This paper developed a miniature 3D vision system for dynamic depth recovery. Our system is constituted by a DOE projector and two cameras. A single pattern with pseudo-random speckles was projected onto the surface of the target object and the coupling pattern was imaged by the stereo cameras. An optimal camera calibration algorithm is adopted to guarantee the measurement accuracy. The speckle pattern projected through a diffractive optical element (DOE) of size 8mm×8mm. The baseline between the stereo cameras is as short as 50mm. The system has the advantages of simple structure, small size, and low cost. It can be easily integrated into mobile devices such as tablet computers and mobile phones. In comparison with several other mature products, the proposed 3D depth camera can achieve 3D reconstruction with higher accuracy.

3D Reconstruction

Bundle adjustment

Stereo cameras

10.1109/robio49542.2019.8961795

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Citations (1)