检索结果-内蒙古大学图书馆

Application of Monocular Direct Vision Odometry in Augmented Reality

Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zuoming Zhang Zixuan Wang Hanwen Wang Xin Wang College of Software Engineering Jilin University Changchun Jilin 130000 China Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun Jilin 130000 China

In recent years, the unlabeled augmented reality system has been gradually applied to various mobile devices, among which stable, accurate, and fast registration is the key to realizing this function. For this technique, this paper introduces camera exposure parameters and puts the data association and pose estimation into a unified nonlinear optimization problem. Moreover, the direct monocular vision odometer is transplanted into the augmented reality system through the position adjustment module. We compare it with the traditional visual odometry method that matches the feature points. The results show that this improved method can be used to track more quickly and build a more visual semi-dense point cloud map, which can be used to support the registration and tracking of virtual objects in augmented reality.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of Hybrid Monocular SLAM Method in Augmented Reality

引用

Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zuoming Zhang Hanwen Wang Man Shu Xin Wang College of Software Engineering Jilin University Changchun Jilin 130000 China Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun Jilin 130000 China

In this paper, we design a hybrid (semi-direct) approach to simultaneous localization and mapping (SLAM) for monocular cameras and apply it to augmented reality (AR) for monocular cameras. We combine the advantagesof the direct method and the feature point method. We use both photometric bundle adjustment which is robust to camera exposure time and motion bundle adjustment which is geometrically robust based on feature points to do tracking process. This approach can maintain an intuitive direct local map as well as a reusable global sparse feature point map. Through the processing of point clouds, such as PCA plane detection and grid reconstruction, we greatly improve the effect of the augmented reality system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Text Categorization Method Based on Improved Mutual Information and Characteristic Weights Evaluation Algorithms

Text Categorization Method Based on Improved Mutual Informat...

引用

International Conference on Fuzzy Systems and knowledge Discovery (FSKD)

作者： Zhili Pei Xiaohu Shi Maurizio Marchese Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China College of Mathematics & Computer Science National University of Inner Mongolia Tongliao China Department of Information and Communication Technology University of Trento Povo TN USA

The improvement of text categorization by statistical methods can be performed from two main directions, namely the feature selection and the evaluation of characteristic weights. In this paper, we propose an enhanced text categorization method based on a modified mutual information algorithm and evaluation algorithm of characteristic weights which improves both aspects. The proposed method is applied to the benchmark test set Reuters-21578 Top10 to examine its effectiveness. Numerical results show that the precision, the recall and the value of F1 of the proposed method are all superior to those of existing conventional methods.

关键词： Text categorization Mutual information Frequency shift keying Frequency estimation Computer science Statistical analysis Testing Educational institutions Communications technology Performance evaluation

来源：评论

学校读者我要写书评

暂无评论

Asymmetric Cross-Scale Alignment for Text-Based Person Search

arXiv

引用

arXiv 2022年

作者： Ji, Zhong Hu, Junhua Liu, Deyin Wu, Lin Yuanbo Zhao, Ye The School of Electrical and Information Engineering Tianjin University Tianjin300072 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230039 China Department of Computer Science Swansea University SA1 8EN United Kingdom The Key Laboratory of Knowledge Engineering with Big Data School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China

Text-based person search (TBPS) is of significant importance in intelligent surveillance, which aims to retrieve pedestrian images with high semantic relevance to a given text description. This retrieval task is characterized with both modal heterogeneity and fine-grained matching. To implement this task, one needs to extract multi-scale features from both image and text domains, and then perform the cross-modal alignment. However, most existing approaches only consider the alignment confined at their individual scales, e.g., an image-sentence or a region-phrase scale. Such a strategy adopts the presumable alignment in feature extraction, while overlooking the cross-scale alignment, e.g., image-phrase. In this paper, we present a transformer-based model to extract multi-scale representations, and perform Asymmetric Cross-Scale Alignment (ACSA) to precisely align the two modalities. Specifically, ACSA consists of a global-level alignment module and an asymmetric cross-attention module, where the former aligns an image and texts on a global scale, and the latter applies the cross-attention mechanism to dynamically align the cross-modal entities in region/image-phrase scales. Extensive experiments on two benchmark datasets CUHK-PEDES and RSTPReid demonstrate the effectiveness of our approach. Codes are available at https://***/mulhjh/ACSA. Copyright © 2022, The Authors. All rights reserved.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

A new SAT Encoding Scheme for Exactly-one Constraints

引用

Journal of Physics: Conference Series 2019年第1期1288卷

作者： Jiatong Cai Yating Su Xixi Yang Jionghao Min Yong Lai College of Software Jilin University Changchun P.R. China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun P.R. China

Exactly-one constraints have comprehensive applications for the fields of artificial intelligence and operations research. For many encoded SAT problems generated by the existing encoding schemes of exactly-one constraints, the state-of-the-art knowledge compilers cannot complete compilation. In this paper, we propose a new encoding scheme of exactly-one constraints. We introduce two-dimensional auxiliary variables (represented as a matrix) to denote the constraint that exactly one of some variables can be assigned as true. The clauses generated by our scheme is significantly less than those generated by three other existing encoding schemes. The experimental results on the exact cover problems show that the encoded CNF formulas generated by our scheme requires less compilation time, compared with the other three coding schemes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Object Attribute Matters in Visual Question Answering

arXiv

引用

arXiv 2023年

作者： Li, Peize Si, Qingyi Fu, Peng Lin, Zheng Wang, Yan School of Artificial Intelligence Jilin University Changchun China Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun China

Visual question answering is a multimodal task that requires the joint comprehension of visual and textual information. However, integrating visual and textual semantics solely through attention layers is insufficient to comprehensively understand and align information from both modalities. Intuitively, object attributes can naturally serve as a bridge to unify them, which has been overlooked in previous research. In this paper, we propose a novel VQA approach from the perspective of utilizing object attribute, aiming to achieve better object-level visual-language alignment and multimodal scene understanding. Specifically, we design an attribute fusion module and a contrastive knowledge distillation module. The attribute fusion module constructs a multimodal graph neural network to fuse attributes and visual features through message passing. The enhanced object-level visual features contribute to solving fine-grained problem like counting-question. The better object-level visual-language alignment aids in understanding multimodal scenes, thereby improving the model’s robustness. Furthermore, to augment scene understanding and the out-of-distribution performance, the contrastive knowledge distillation module introduces a series of implicit knowledge. We distill knowledge into attributes through contrastive loss, which further strengthens the representation learning of attribute features and facilitates visual-linguistic alignment. Intensive experiments on six datasets, COCO-QA, VQAv2, VQA-CPv2, VQA-CPv1, VQAvs and TDIUC, show the superiority of the proposed method. © 2023, CC BY.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

Consistency label-activated region generating network for weakly supervised medical image segmentation

引用

Computers in Biology and Medicine 2024年 173卷 108380-108380页

作者： Du, Wei Huo, Yongkang Zhou, Rixin Sun, Yu Tang, Shiyi Zhao, Xuan Li, Ying Li, Gaoyang Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun130012 China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East Hospital Shanghai200092 China Bioinformatics Department School of Life Sciences and Technology Tongji University Shanghai200092 China

The current methods of auto-segmenting medical images are limited due to insufficient and ambiguous pathonmorphological labeling. In clinical practice, rough classification labels (such as disease or normal) are more commonly used than precise segmentation masks. However, there is still much to be explored regarding utilizing these weak clinical labels to accurately determine the lesion mask and guide medical image segmentation. In this paper, we proposed a weakly supervised medical image segmentation model to directly generate the lesion mask through a class activation map (CAM) guided cycle-consistency label-activated region transferring network. Cycle-consistency enforces that the mappings between the two domains should be reversible, which ensures that the original image can be reconstructed from the translated image. We developed a complementary branches fusion module to address the issue of blurry boundaries in CAM-guided segmentation. The complementary branch preserves the original semantic information of the non-lesion region and perfectly fuses the transferred feature of the lesion region with a complementary mask-constrained fake image generation process to clear the boundary of the lesion and non-lesion regions. This module allows the class transformation to focus solely on the label-activated region, resulting in more explicit segmentation. This model can accurately identify different region of medical images at the pixel-level while preserving the overall semantic structure semantion. It organizes disease labels and corresponding regions during image synthesis. Our method utilizes a joint discrimination strategy that significantly enhances the precision of the produced lesion mask. Extensive experiments of the proposed method on BraTs, ISIC and COVID-19 datasets demonstrate superior performance over existing state-of-the-art methods. The code and datasets are available at: https://***/mlcb-jlu/MedImgSeg. © 2024 Elsevier Ltd

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Dataset-Level Color Augmentation and Multi-Scale Exploration Methods for Polyp Segmentation

SSRN

引用

SSRN 2024年

作者： Chen, Haipeng Ju, Honghong Qin, Jun Song, Jincai Lyu, Yingda Liu, Xianzhu College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computer Science and Technology Changchun University of Science and Technology Changchun130022 China Public Computer Education and Research Center Jilin University Changchun130012 China National and Local Joint Engineering Research Center of Space Optoelectronics Technology Changchun University of Science and Technology Changchun130022 China College of Opto-Electronic Engineering Changchun University of Science and Technology Changchun130022 China

Automatic segmentation of polyps from colonoscopy images plays a critical role in early screening and treatment of colorectal cancer. Although deep learning methods have made significant progress, precise polyp segmentation faces two challenges: (1) the imbalance of color appearances in the limited training dataset hinders the generalization of the model, and (2) polyps have the diverse scales, locations and shapes with blurred boundary. To address the issues, Dataset-Level Color Augmentation (DLCA) and Convolutional Multi-scale Attention Module (CMAM) are proposed. DLCA employs the dataset-level color knowledge and generate new color appearances, to avoid the model learning false associations with colors. Meanwhile, CMAM simultaneously explores the region and boundary clues and model multi-scale context, which improves the accuracy of polyp localization and fine-grained segmentation. We conduct comprehensive experiments and compare our network with state-of-the-art methods. The proposed model is superior on multiple polyp datasets, especially on ETIS, where mDice and mIoU reach 0.839 and 0.766. Furthermore, it's validated that DLCA can be widely applied to most polyp segmentation methods, and CMAM is practical and plug-and-play. Finally, the model demonstrates promising generalization to breast ultrasound and skin lesion segmentation. © 2024, The Authors. All rights reserved.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Intensity preserving technology in image restoration

引用

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (engineering and Technology Edition) 2013年第SUPPL.1期43卷 106-109页

作者： Guo, Xiao-Xin Xu, Zhi-Wen Che, Xiang-Jiu College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

A new approach of image restoration for the sequence of fluorescein angiography was proposed. First, the intensity constraint was incorporated into Miller regularization equation to obtain the ability to preserve the high intensity of pixels. Thus, the restored image would be influenced not only by the smoothness constraints, but also by the intensity constraints. Secondly, in the process of the restoration, we use an intensity template obtained from the pre-filtering procedure was used to achieve the intensity constraints. The template represented an image composed by the desired intensity value. The experiments show that the proposed scheme gains a better result in both high intensity preservation and image restoration.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Optical flow computation based on spline functionals

引用

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (engineering and Technology Edition) 2013年第SUPPL.1期43卷 165-168页

作者： Guo, Xiao-Xin Yang, Guang Xu, Zhi-Wen College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

A mathematical model using the spline functional as smooth constraints was presented. The second-and fourth-order partial differential equations constraints were two special cases in the model. The necessary condition for optical flow minimization problem solution was also presented. This model provided a basis for formal representation and numerical computation of optical flow from a methodological point of view. The significance of this mathematical model lay in the simplification of the equations for optical flow computation into linear algebraic equations. The simplification can contribute to discrete representation of the optical flow equation, and also verify that the use of smoothness constraints can ensure the existence and uniqueness of the solution from the view of the algebraic equations.

关键词： Optical flows

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：