Article
Computer Science, Information Systems
Yunbai Qin, Jialiang Li, Pinqun Jiang, F. Jiang
Summary: The paper introduces a novel stitching method that locates overlapped regions and records feature points, guides image warping with a local warp model and arc function weight model, showing better performance than other state-of-the-art methods. The approach effectively improves matching efficiency, eliminates color difference and ghosting, and maintains accuracy and stability in complex scenes.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yinqi Chen, Huicheng Zheng, Yiyan Ma, Zhiwei Yan
Summary: This paper proposes a new method for image stitching using angle correspondences, which can generate correct warping in overlapping regions and prevent distortion in non-overlapping areas effectively. Compared to existing methods, it yields more accurate results with significantly less artifacts.
PATTERN RECOGNITION
(2021)
Article
Environmental Sciences
Jun Chen, Zixian Li, Chengli Peng, Yong Wang, Wenping Gong
Summary: This paper introduces an image stitching method for Unmanned Aerial Vehicles (UAV) using the optimal seam algorithm and half-projective warp, which effectively retains the original information of the image and achieves the desired stitching effect.
Article
Geochemistry & Geophysics
Ariyan Zarei, Emmanuel Gonzalez, Nirav Merchant, Duke Pauli, Eric Lyons, Kobus Barnard
Summary: This paper addresses the challenge of fast image stitching for large image collections while effectively dealing with drift and minimal overlap. The authors propose a method that focuses on scientific applications and prioritizes ground-truth accuracy. They present approaches for both affine and homography transformations and demonstrate the superiority of their method through evaluations on various datasets. The authors also provide valuable ground-truth datasets for further research in this field.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Computer Science, Information Systems
Zaifeng Shi, Pumeng Wang, Qingjie Cao, Cheng Ding, Tao Luo
Summary: This paper proposes a misalignment-eliminated warping image stitching method based on grid-based motion statistics (GMS) matching. The method uses a matching approach from coarse to fine and employs local homography with global similarity constraint for image warping, achieving accurate alignment while maintaining a natural look.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Biology
Gayathri Mahalingam, Russel Torres, Daniel Kapner, Eric T. Trautman, Tim Fliss, Shamishtaa Seshamani, Eric Perlman, Rob Young, Samuel Kinn, JoAnn Buchanan, Marc M. Takeno, Wenjing Yin, Daniel J. Bumbarger, Ryder P. Gwinn, Julie Nyhus, Ed Lein, Steven J. Smith, R. Clay Reid, Khaled A. Khairy, Stephan Saalfeld, Forrest Collman, Nuno Macarico da Costa
Summary: Serial-section electron microscopy is a high-resolution method for studying biological samples, with applications in reconstructing neural wiring diagrams. We present ASAP, a software pipeline that can handle large datasets in a distributed computational environment, offering high throughput and modular design.
Article
Computer Science, Artificial Intelligence
Qiang Zhao, Yike Ma, Chen Zhu, Chunfeng Yao, Bailan Feng, Feng Dai
Summary: In this paper, a new deep neural network for image stitching with small parallax images is proposed, with key components designed to improve performance and a new loss function introduced. Experimental results demonstrate that the method outperforms existing methods in terms of quantitative evaluation, visual stitching result, and robustness.
Article
Computer Science, Information Systems
Lei Zhang, Hua Huang
Summary: This paper presents a manifold optimization method for image stitching by treating spatial transformations as elements of a prescribed matrix manifold. The proposed method computes spatially varying homographies for alignment and performs interpolation between homography and similarity transformation to mitigate distortion. Experimental results demonstrate that our method outperforms other methods for image stitching.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Engineering, Electrical & Electronic
Mingyuan Lin, Tangbo Liu, Ying Li, Xinpeng Miao, Chu He
Summary: Image stitching aims to generate a panorama with a larger field of view by warping and aligning two or more images with overlapping areas. This paper proposes a multi-plane alignment algorithm guided by the disparity map for images with large parallax. The concept of average tolerable parallax is introduced to distinguish background planes and foreground objects. An optimal homography estimation method based on relative projection biases is proposed to obtain reliable disparity maps. Experimental results demonstrate the accuracy and superiority of the algorithm compared to existing methods.
Article
Computer Science, Information Systems
Jialiang Li, Dong Wu, Pinqun Jiang, Zili Li, Shuxiang Song
Summary: The accuracy of image warping is crucial for image stitching, and this paper introduces a multi-plane alignment method based on superpixel segmentation and line features to improve matching accuracy. This method outperforms some state-of-the-art warps in both qualitative and quantitative aspects, demonstrating its effectiveness in image alignment.
Article
Physics, Multidisciplinary
Yizhi Cong, Yan Wang, Wenju Hou, Wei Pang
Summary: Feature detection and correct matching are crucial for image stitching. Existing methods often suffer from insufficient matching points in low-textured or repetitively-textured areas. This paper proposes a novel approach that increases feature correspondences and optimizes hybrid terms to eliminate misalignment. The method also mitigates projection distortion and perspective distortion, achieving accurate alignment and reduced distortion.
Article
Chemistry, Multidisciplinary
Surendra Kumar Sharma, Kamal Jain, Anoop Kumar Shukla
Summary: Image stitching is a commonly used technique in image processing and computer vision applications. This paper presents a comparative analysis of feature detectors and descriptors for image stitching, considering the number of matched points, time taken, and quality of stitched image. The results suggest that using AKAZE with AKAZE can be preferable in most situations.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Manufacturing
Tianqi Gu, Chenjie Hu, Dawei Tang, Shuwen Lin, Tianzhi Luo
Summary: The study presents an improved method named as alpha-MTLS, which uses the TLS method and introduces a geometric characteristic parameter alpha to reduce the influence of outliers effectively, resulting in higher fitting accuracy and robustness compared to traditional MLS and MTLS methods.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2021)
Article
Computer Science, Artificial Intelligence
Xingsheng Yuan, Yongbin Zheng, Wei Zhao, Jiongming Su, Jianzhai Wu
Summary: In this study, a method for image stitching using point features and line features integrated into a designed energy function was proposed to address the challenges of traditional methods. Additionally, a global colour consistency optimization method was introduced. Experimental results showed that the proposed method achieved satisfying results in image alignment and colour consistency.
IET IMAGE PROCESSING
(2021)
Article
Computer Science, Hardware & Architecture
Zhong Qu, Jun Li, Le-yuan Gao
Summary: This paper presents an effective and adaptive method for rotating images to an appropriate angle before stitching to solve the problem of stitching overlapped images taken under different rotation angles. The method involves partitioning the target image into four parts and extracting features to match them with a reference image. The rotation angle is adjusted based on the part with the most matching pairs, and the direction of matching pairs is detected to further refine the rotation angle. Experimental results demonstrate the effectiveness and satisfactory stitching result of the proposed method.
Article
Computer Science, Artificial Intelligence
Pulak Purkait, Tat-Jun Chin, Alireza Sadri, David Suter
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2017)
Article
Computer Science, Artificial Intelligence
Tat-Jun Chin, Pulak Purkait, Anders Eriksson, David Suter
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2017)
Article
Computer Science, Artificial Intelligence
Hanzi Wang, Guobao Xiao, Yan Yan, David Suter
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2019)
Article
Computer Science, Artificial Intelligence
Guobao Xiao, Hanzi Wang, Yan Yan, David Suter
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2019)
Article
Psychiatry
Diana Weiting Tan, Murray T. Maybery, Syed Zulqarnain Gilani, Gail A. Alvares, Ajmal Mian, David Suter, Andrew J. O. Whitehouse
TRANSLATIONAL PSYCHIATRY
(2020)
Article
Computer Science, Artificial Intelligence
Huu Le, Tat-Jun Chin, Anders Eriksson, Thanh-Toan Do, David Suter
Summary: Maximum consensus estimation is crucial in robust fitting problems in computer vision. Existing algorithms either provide rough approximate solutions cheaply or exact solutions at a high cost. This paper proposes deterministic algorithms to approximately optimize the maximum consensus criterion, filling the gap between the two extremes. The algorithms, based on convex subproblem solving, greatly improve rough initial estimates and are practical for realistic input sizes.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2021)
Article
Behavioral Sciences
Diana Weiting Tan, Syed Zulqarnain Gilani, Maryam Boutrus, Gail A. Alvares, Andrew J. O. Whitehouse, Ajmal Mian, David Suter, Murray T. Maybery
Summary: In this study, greater facial asymmetry was found in parents of autistic individuals compared to age-matched adults without a family history of ASD. This suggests that the broad autism phenotype may manifest as facial asymmetry through heritability factors.
Article
Engineering, Civil
Weiqin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad, David Suter, Alireza Bab-Hadiashar
Summary: Autonomous vehicles in intelligent transportation systems require reliable and safe navigation, which relies on accurate object detection and depth estimation. However, the accuracy of disparity estimation does not directly translate to the accuracy of depth estimation, especially at large distances. In order to address this issue, we propose a pair of depth-based loss functions for foreground objects and background, and demonstrate their effectiveness through extensive experiments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Medicine, General & Internal
Naeha Sharif, Syed Zulqarnain Gilani, David Suter, Siobhan Reid, Pawel Szulc, Douglas Kimelman, Barret A. Monchka, Mohammad Jafari Jozani, Jonathan M. Hodgson, Marc Sim, Kun Zhu, Nicholas C. Harvey, Douglas P. Kiel, Richard L. Prince, John T. Schousboe, William D. Leslie, Joshua R. Lewis
Summary: This study trained and tested a convolutional neural network (CNN) algorithm for automated scoring of abdominal aortic calcification (AAC-24) and validated its consistency with scores from trained imaging specialists. The results showed that ML-AAC-24 scores were significantly associated with the risk of cardiovascular events in a real-world setting, indicating that this approach could improve the identification of individuals at high risk of cardiovascular disease in clinical settings.
Proceedings Paper
Cardiac & Cardiovascular Systems
Najmeh Fayyazifar, Selam Ahderom, David Suter, Andrew Maiorana, Girish Dwivedi
2020 COMPUTING IN CARDIOLOGY
(2020)
Article
Computer Science, Artificial Intelligence
Sundaram Muthu, Ruwan Tennakoon, Tharindu Rathnayake, Reza Hoseinnezhad, David Suter, Alireza Bab-Hadiashar
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2020)
Proceedings Paper
Computer Science, Theory & Methods
Giang Truong, Syed Zulqarnain Gilani, Syed Mohammed Shamsul Islam, David Suter
2019 DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Shuyuan Lin, Guobao Xiao, Yan Yan, David Suter, Hanzi Wang
THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Qianggong Zhang, Tat-Jun Chin, David Suter
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)
(2017)
Article
Computer Science, Artificial Intelligence
Taotao Lai, Hanzi Wang, Yan Yan, Guobao Xiao, David Suter
COMPUTER VISION AND IMAGE UNDERSTANDING
(2017)